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• Write and defend diagnostic SQL queries against large-scale production datasets • Build and maintain ingestion pipelines for bid, win, and impression logs into BigQuery • Harmonize fields across independently designed datasets and maintain versioned field mappings • Develop point-in-time-correct feature tables and aggregation pipelines • Design and maintain conversion and labeling pipelines with delayed label handling • Own the data serving write path, schema contracts, publishing flows, and freshness SLOs • Build experimentation infrastructure including traffic splitting and reporting pipelines • Perform large-scale historical backfills and safe reprocessing after mapping changes • Implement data isolation and safe-aggregation controls for advertiser data protection • Develop automated data quality validation frameworks • Collaborate closely with Customer engineers and prepare operational documentation • Contribute to architecture discussions and platform scalability improvements • 5+ years of experience in Data Engineering • At least 2 years of experience working with production ML or large-scale analytics pipelines • Expert-level SQL skills including window functions and incremental processing patterns • Strong Python skills for production-grade pipeline development • Hands-on experience with Spark or PySpark • Experience designing ETL / ELT pipelines with Airflow, Cloud Composer, Dagster, or similar tools • Experience working with cloud data warehouses at scale, preferably BigQuery • Strong understanding of data modeling and point-in-time correctness • Experience working with event-driven or clickstream datasets at very large scale • Experience supporting business-critical production pipelines • Upper-Intermediate English level or higher WILL BE A PLUS • Experience with GCP services including Dataflow, Pub/Sub, GCS, and Beam • Experience building streaming or near-real-time ingestion systems • Understanding of feature stores, train/serve skew, and label leakage prevention • Experience in AdTech or auction-based environments • Experience handling delayed or incomplete labels in ML systems • Experience with dbt or similar transformation frameworks • Experience delivering solutions into Customer-owned infrastructure • Knowledge of GDPR/CCPA-related privacy engineering practices • Experience with experimentation infrastructure and statistical validation pipelines • Experience working in hybrid cloud/on-prem Linux environments • Terraform and Kubernetes experience • Experience optimizing warehouse cost and performance PERSONAL PROFILE • Strong analytical and problem-solving skills • Ownership-oriented mindset • Ability to work independently in a client-facing environment • Strong communication and documentation skills • Comfortable working in a fast-paced engineering environment • Collaborative and proactive attitude Join Sigma Software to build large-scale data infrastructure powering a real-time AdTech platform processing hundreds of millions of auction requests daily. We are looking for a Senior Data Engineer who enjoys solving complex distributed data challenges and building production-grade ML-oriented data systems. You will become part of a dedicated Sigma Software team developing predictive modeling and optimization capabilities for a live advertising ecosystem. The role combines large-scale event processing, streaming and batch pipelines, experimentation infrastructure, and high-throughput data engineering in a cloud-native environment. We as a company offer the opportunity to work on impactful global products, collaborate with experienced engineers, and contribute to architecture decisions while growing your expertise in large-scale distributed systems and modern data platforms. CUSTOMER Our Customer is a technology company operating supply-side infrastructure within the programmatic advertising ecosystem. The company manages a large-scale ad exchange handling hundreds of millions of auction requests per day and is actively investing in predictive decisioning technologies to optimize advertising outcomes in real time. PROJECT The project focuses on building a predictive modeling and optimization platform on top of a live ad exchange environment. The platform performs real-time supply scoring and filtering, contextual performance estimation, look-alike audience generation, and multi-objective optimization under business constraints. The solution processes massive-scale event and auction datasets and includes feature engineering pipelines, streaming and batch ingestion, experimentation infrastructure, point-in-time-correct training data generation, and ML-oriented data services with strict operational reliability and compliance requirements.

The project We are seeking a talented Cloud Engineer to join our client's team and provide support with cloud deployment and maintenance tasks. As part of our international team, you will contribute to the seamless operation of our cloud infrastructure, ensuring optimal performance and reliability for our clients. Our client specializes in innovative software solutions for safety-critical control and communication technology in public safety, transport, air traffic, maritime, and defense sectors with a focus on incident and crisis management in global settings. Our projects are technically and organizationally challenging and require a high level of expertise. As a Cloud Engineer, you will be responsible for deploying and administering cloud environments, leveraging Infrastructure as Code (IaC) principles using Terraform. You will work closely with our team to ensure the successful deployment and maintenance of cloud-based solutions, with a focus on Azure environments. Additionally, you will utilize your expertise in Kubernetes and DevOps practices to optimize our cloud infrastructure and enhance security measures. Industry: safety-critical control and communication technology The number of open vacancies: 1 Type of contract: B2B/labour contract The preferred scale of work : full time Start date: asap Type of work: 100% remote from Poland Location: Poland Main technologies used in the project: • Infrastructure as Code (IaC) with Terraform. • Azure services for cloud deployment and administration. • Kubernetes for container orchestration and management. • DevOps practices and tools (excluding Azure DevOps). • Security implementation via manual methods or self-written Infra as Code.

Addepto is a leading AI consulting ( https://addepto.com/ai-consulting/ ) and data engineering ( https://addepto.com/data-engineering-services/ ) company that builds scalable, ROI-focused AI solutions for some of the world's largest enterprises and pioneering startups, including Rolls Royce, Continental, Porsche, ABB, and WGU. With an exclusive focus on Artificial Intelligence and Big Data, Addepto helps organizations unlock the full potential of their data through systems designed for measurable business impact and long-term growth. The company's work extends beyond client engagements. Drawing from real-world challenges and insights, Addepto has developed its own product - ContextClue - and actively contributes open-source solutions to the AI community. This commitment to transforming practical experience into scalable innovation has earned Addepto recognition by Forbes as one of the top 10 AI consulting companies worldwide . As part of KMS Technology , a US-based global technology group, Addepto combines deep AI specialization with enterprise-scale delivery capabilities—enabling the partnership to move clients from AI experimentation to production impact, securely and at scale. As a Junior Data Engineer , you will have the exciting opportunity to work with a team of technology experts on challenging projects across various industries, leveraging cutting-edge technologies. Here are some of the projects we are seeking talented individuals to join: • Design and development of the client's Azure Data Platform to modernize and optimize critical processes. Key activities involve migrating selected SSAS cube objects and SSIS pipelines from the on-premises SQL Server to Azure Cloud Resources while ensuring data integrity, completeness, and operational readiness of the client's data processes. Operational efficiency will be enhanced by improving the UI/UX, unifying logging, setting up monitoring and alerts, and automating Power BI reports and workspace management. Additionally, backup strategies, cost management, and documentation will be established to ensure robust, scalable, and maintainable platform operations. • Design and development of a universal data platform for global aerospace companies . This Azure and Databricks-powered initiative combines diverse enterprise and public data sources. The data platform is at the early stages of the development, covering design of architecture and processes as well as giving freedom for technology selection. • Data Platform Transformation for energy management association body. This project addressed critical data management challenges, boosting user adoption, performance, and data integrity. The team is implementing a comprehensive data catalog, leveraging Databricks and Apache Spark/PySpark, for simplified data access and governance. Secure integration solutions and enhanced data quality monitoring, utilizing Delta Live Table tests, established trust in the platform. The intermediate result is a user-friendly, secure, and data-driven platform, serving as a basis for further development of ML components. Your main responsibilities: • Write advanced SQL queries and develop database procedures. • Create data visualizations using Power BI to deliver actionable insights. Design and develop ETL processes, Data Warehouses, Data Marts, and Data Lakes. • Gather and analyze requirements to design logical and physical data models. • Work with various data storage and database technologies to build scalable solutions. • Deploy data applications using Docker, Kubernetes, and GitHub. • Take ownership of assigned tasks and actively contribute to project and product development.

• Are you passionate about esports and enjoy turning complex tournament plans into well-executed live events? • Do you enjoy coordinating people, systems and deadlines to deliver tournaments successfully? • Are you confident managing operational risks, solving problems under pressure and keeping stakeholders aligned? • Do you take ownership of projects and enjoy seeing them through from initial planning to live delivery? • Do you want to play a key role in delivering high-quality tournament experiences for teams, partners and fans? If the answers to the above questions are yes, then this role could be ideal for you! GRID is looking for a Tournament Coordinator to join our Tournament Services team and take operational ownership of assigned tournaments from initial planning and design through to live delivery and post-event review. You will be responsible for translating tournament objectives, approved designs and commercial requirements into clear, executable operational plans. You will coordinate the people, teams, systems and dependencies required to make each tournament successful, while maintaining event readiness, managing operational risks and keeping stakeholders aligned throughout the tournament lifecycle. You will act as the primary operational point of contact for your assigned tournaments, working closely with GRID teams including Tournament Services, League Operations, Tournament Production, Partnerships, Integrity, Support and Commercial, as well as publishers, esports teams, partners and other tournament stakeholders. The role combines tournament operations, project coordination, stakeholder management and live event delivery. You will be expected to manage multiple workstreams simultaneously, identify risks and blockers early, drive actions to completion and make sure every part of the tournament is ready for successful delivery.

Why Join Exadel We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks. From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next. What powers it all? Our people are ambitious, collaborative, and constantly evolving. What You'll Do • Design and develop engaging digital learning experiences with a strong focus on AI-related learning content • Analyze training needs and define suitable learning solutions for self-paced and blended formats • Work with stakeholders and subject matter experts to define learning goals, target audiences, and success criteria • Structure learning journeys, courses, practical activities, assessments, and supporting materials • Transform complex technical and business information into clear, practical, and learner-friendly content • Develop courses directly in Sana Learn LMS using its built-in authoring and engagement features • Create video scripts, knowledge checks, practice tasks, assessments, and job aids • Use Synthesia to develop AI-avatar videos when required • Review and continuously improve learning content based on feedback, learner experience, and business needs • Ensure learning materials are accurate, engaging, well-structured, and aligned with adult learning principles • Collaborate with the L&D team and LMS administrator throughout the content development and publishing process What You Bring • Experience in instructional design, e-learning development, corporate training, or learning content creation • Understanding of adult learning principles and instructional design basics • Ability to translate business needs and behavior-change goals into effective learning solutions • Strong skills in structuring information and simplifying complex content • Experience working with subject matter experts and stakeholders • Ability to write clear, engaging, and learner-friendly learning content • Familiarity with LMS platforms, authoring tools, or digital learning environments • Good communication, collaboration, and feedback-management skills • Strong attention to detail and ability to maintain content quality • Ability to work independently, manage priorities, and meet deadlines • Willingness to learn new AI-enabled learning tools and technologies English level Intermediate+ Legal & Hiring Information • Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more. • Reasonable accommodations are available to enable individuals with disabilities to perform essential functions. • Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs. • Compensation details are shared with candidates at the early stage of the recruitment process. • The offer is not binding until a signed contract is in place. Your Benefits at Exadel Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details. • International projects • In-office, hybrid, or remote flexibility • Medical healthcare • Recognition program • Ongoing learning & reimbursement • Well-being program • Team events & local benefits • Sports compensation • Referral bonuses • Top-tier equipment provision Exadel Culture We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matter.

• Build and maintain ML training orchestration pipelines across hourly, daily, and weekly schedules • Implement retries, backfills, and idempotent execution mechanisms • Design and support model registry workflows including versioning, lineage, evaluation gates, and promotion processes • Develop isolated per-advertiser model environments with namespace and configuration separation • Build scalable refresh pipelines and publishing workflows for serving infrastructure • Implement shadow mode and champion/challenger deployment strategies • Develop monitoring and alerting for ML-specific metrics including feature drift, prediction drift, train/serve skew, and calibration decay • Ensure reproducibility of ML workflows using containerized environments, pinned dependencies, and data snapshots • Monitor training and scoring costs across tenants • Collaborate with DevOps and SRE engineers on CI/CD and infrastructure automation • Prepare operational documentation and platform handover materials • 5+ years of experience in MLOps, ML platform engineering, or infrastructure engineering supporting production ML systems • Strong Python skills and experience building platform-level tooling and automation • Hands-on experience with Kubernetes and Docker • Experience building CI/CD pipelines for ML workloads • Hands-on production experience with MLflow, Kubeflow, Airflow, Argo Workflows, Vertex Pipelines, or similar orchestration and ML lifecycle platforms • Experience with ML platforms and model lifecycle tools such as Vertex AI, MLflow, or Kubeflow • Strong understanding of ML observability including drift detection, train/serve skew monitoring, and incident response • Experience designing or supporting multi-tenant ML systems and isolated model environments • Experience working with cloud platforms, preferably GCP • Experience with infrastructure-as-code tools such as Terraform • Experience with Linux environments • Understanding of the ML lifecycle and productionization processes • Upper-Intermediate English level or higher WILL BE A PLUS • Experience with feature stores and feature consistency management • Experience with large-scale batch scoring systems operating under freshness SLAs • Familiarity with experiment tracking platforms and evaluation gates • Experience with on-premises Kubernetes or bare-metal Linux infrastructure • Knowledge of DVC, lakeFS, or other data versioning tools • Experience with Bigtable, Redis, Aerospike, or similar low-latency serving databases • GPU scheduling and training cost optimization experience • Familiarity with SOC 2, ISO 27001, or GDPR-related compliance requirements PERSONAL PROFILE • Strong ownership mindset and focus on operational reliability • Ability to work independently in complex distributed systems environments • Strong collaboration and communication skills • Analytical thinking with attention to scalability and maintainability • Comfortable working in fast-paced product-oriented environments We are looking for a Senior MLOps Engineer to join Sigma Software and help build a production-grade ML platform for a large-scale AdTech ecosystem. You will work on infrastructure powering predictive decision-making systems that process hundreds of millions of auction requests daily. As part of a dedicated engineering team, you will contribute to scalable ML orchestration, model lifecycle automation, observability, and real-time optimization workflows. This role is ideal for engineers with strong production experience who enjoy solving complex platform and operational challenges. We at Sigma Software offer the opportunity to work on cutting-edge ML infrastructure projects, collaborate with experienced engineers, and influence architecture decisions in a long-term strategic engagement. CUSTOMER Our Customer is a technology company operating supply-side infrastructure within the programmatic advertising ecosystem. The company manages a high-load ad exchange platform handling hundreds of millions of auction requests every day and is investing in advanced predictive decision-making capabilities to improve advertiser outcomes and real-time optimization processes. PROJECT Sigma Software is building a predictive modeling and optimization platform integrated with a live ad exchange environment. The solution enables real-time supply scoring and filtering, audience look-alike generation, contextual performance estimation, and multi-objective optimization under operational constraints. The project combines large-scale ML infrastructure, automated model lifecycle management, multi-tenant architecture, and advanced observability practices. The team focuses on delivering reliable, reproducible, and scalable ML systems ready for long-term Customer ownership. Key Technologies: Python, Kubernetes, Docker, GCP, Vertex AI, MLflow, Airflow, Kubeflow, Argo Workflows, Terraform

About Us Axelera AI https://www.axelera.ai is not your regular deep-tech company. We are creating the next-generation AI platform to support anyone who wants to help advancing humanity and improve the world around us. In just five years, we have raised a total of $450 million and have built a world-class team of 250+ employees (including 60+ PhDs with more than 40,000 citations), both remotely from 20 different countries and with offices in Belgium, France, Switzerland, Italy, the UK, headquartered at the High Tech Campus in Eindhoven, Netherlands. We have also launched our Metis™ AI Platform, which achieves a 3-5x increase in efficiency and performance, and have visibility into a strong business pipeline exceeding $100 million. Our unwavering commitment to innovation has firmly established us as a global industry pioneer. Are you up for the challenge? Position Overview We're looking for an AI System Engineer to help build and maintain Axelera Wingman and Axelera's agentic AI platform. You'll develop the agent capabilities, execution environments and software integrations that make the platform reliable and useful. Deploying models and running AI workloads will help you validate the platform, identify gaps and improve the product. Key responsibilities: • Build reliable agent systems, intelligent tools and application integrations • Develop secure, scalable execution environments for demanding AI workloads • Build and maintain Wingman's platform capabilities, including access to accelerated computing and remote workload execution • Deploy and optimize computer vision models, LLM services and inference infrastructure to validate Axelera's agentic AI platform • Own capabilities from implementation and hardware validation through production operation • Take ownership of implementation, verification and ongoing reliability • Test functionality, security boundaries, hardware behavior and failure recovery • Write clear documentation, reproducible setup instructions and practical operational runbooks • Become productive quickly with unfamiliar tools, SDKs and systems • Collaborate effectively and exercise sound technical judgment Qualifications Required: Agent Systems & Effective Agent Use • Practical experience building with AI agents, model APIs and tools • Understanding of how agents interact with applications, manage state and recover from failures • Ability to use coding agents effectively to scope, implement and verify work while retaining ownership of correctness and technical decisions • Experience with tool calling, structured outputs, streaming or MCP Compute Platforms & Secure Workload Execution • Understanding of how AI workloads run across applications, hosts and accelerated hardware, including remotely hosted environments • Comfort working with Linux, processes, resource allocation and diagnosing failures across the software and compute stack • Application of sound security principles to permissions, credentials and workload isolation • Ability to build reliable execution with clear progress, cancellation and recovery Model Deployment & Platform Validation • Hands-on experience deploying computer vision models and working with LLM services • Ability to use representative applications and inference workloads to verify platform correctness on real hardware • Skills to assess accuracy, latency, throughput and resource use • Experience investigating failures across model code, inference SDKs and execution environments We value demonstrated ability and judgment over particular degrees or certifications Nice to have: Software Engineering: Python, Rust or another systems language. APIs, databases and native integrations. TypeScript/React and Tauri experience Workload Orchestration: Job submission, scheduling, quotas, concurrency. Result retrieval and reproducible environments. SDK and driver compatibility management Security: Authentication, authorization, least privilege. Access revocation, sandboxing, network security. Protection of users' files and data Cloud Operations (Google Cloud/AWS): Containers, infrastructure as code, CI/CD. Monitoring, incident investigation. Safe deployments, rollback and recovery Applied ML & Accelerated Computing: PyTorch/ONNX. Image/video processing, detection, classification, segmentation. Calibration, quantization and hardware-aware optimization Evaluation & Retrieval: Reproducible benchmarks for model quality, agent behavior and task success. Grounded retrieval and traceable results Additional Strengths: • Fine-tuning, multimodal applications, distributed inference • Desktop packaging • Experience maintaining developer tools Location We offer a flexible working arrangement, with options to: • Work from one of our Axelera AI offices (Florence and Milan in Italy, Amsterdam and Eindhoven in the Netherlands, Leuven in Belgium, Paris in France, Zurich in Switzerland, or Bristol in the United …

About Toptal Toptal is a global network of top talent in business, design, and technology that enables companies to scale their teams, on-demand. With $200+ million in annual revenue and team members based around the globe , Toptal is the world’s largest fully remote workforce . We take the best elements of virtual teams and combine them with a support structure that encourages innovation, social interaction, and fun. We see no borders, move at a fast pace, and are never afraid to break the mold. Position Description: As SVP, Product, you will shape the vision as to where Toptal’s products and platforms go next and then drive the execution to build them. This is the most senior product role in the company. You will report to the Chief Executive Officer, sit on the executive team, and work collaboratively with our Engineering, Design, Finance, Marketing, New Businesses, Professional Services, and Customer leaders. AI is not a line item on your roadmap. It is the roadmap. You should be Toptal’s foremost expert on what AI means for products and platforms. That means real depth in fine-tuning and post-training, agent design and evaluation, and the economics of running models in production, along with the judgment to know which applies to us. Work directly with our AI researchers rather than through them. We expect both the AI agenda and the product strategy to originate with you. We will react to your plan rather than hand you ours. This is a hands-on role. You will write your own specs and pull your own data. When you think an agent could take over a piece of work, you will build a rough version and find out whether it holds up before anyone budgets for it. You will sit in product reviews and say what you actually think. We move fast, and we need Product setting the pace. You will own and set the standards for the hiring bar for the product team, bringing in talent that will advance Toptal to the next level. Your remit runs across the business: the core platform, the talent and client experiences, the internal systems that run it, the products we take to market, and the data and AI platform underneath them. You will work hand in hand with Engineering on the platform all of it runs on, fold acquisitions and new products into the portfolio, and know growth marketing cold, because how a product reaches the market is part of building it. Product is yours to shape at blazing speed: scoping, sizing the teams, planning headcount, and defining the role and the bar for every seat. None of that is beneath the role, and we are not interested in someone who thinks these tasks can be done properly by handing them off to HR. Hiring is the highest-leverage work you do, and we want someone who is visibly excited about landing an A player and treats an open seat as urgent. Your own dedication and hard work will set the tone, and the people you bring in should be inspired to do the best work of their careers on this team. We are looking for the person who will define what an AI-native product organization looks like and then run it successfully. This is a remote position. Resumes and communication must be submitted in English. Responsibilities: The following information is intended to describe the general nature and level of work being performed. It is not intended to be an exhaustive list of all duties, responsibilities, or required skills. AI and agentic product • Own Toptal’s AI product strategy: where agents and models belong across the marketplace, the talent and client experiences, our internal systems, and the products we take to market, along with the business outcomes they carry. • Decide what we build with AI and what we do not, including build-versus-buy on models and tooling and the packaging and pricing of AI-enabled products. • Make AI quality measurable through evals, acceptance bars, and review loops, and partner with Engineering on the platform as its most demanding customer. • Rebuild how Product works using AI, raising the output and judgment of every product manager through AI-assisted discovery, research, prototyping, and analysis. Product managers have to want this rather than comply with it, and creating that pull is on you. Portfolio and operating model • Own the vision, strategy, and multi-year roadmap for the whole portfolio: what we build, what we sunset, and how investment is distributed across growth, platform, and operational leverage. • Establish the product operating model and the metrics behind it, so decisions are made on evidence and user research rather than opinion. • Own the product integration of acquisitions and new products, and act as a senior voice of the customer for both talent and clients. Team and accountability • Decide what a product team should look like now that the roles have blurred, where the product manager believes they can design and code, the engineer believes they can do product and design, and the designer believes they can code and do product. …

About Toptal Toptal is a global network of top talent in business, design, and technology that enables companies to scale their teams, on-demand. With $200+ million in annual revenue and team members based around the globe , Toptal is the world’s largest fully remote workforce . We take the best elements of virtual teams and combine them with a support structure that encourages innovation, social interaction, and fun. We see no borders, move at a fast pace, and are never afraid to break the mold. Position Description: As Chief Technology Officer, you will drive execution for the product and engineering teams and put AI at the core of everything the company builds. You will own Toptal’s full technical architecture and you will build it AI-first—utilizing best practices for agentic engineering. AI is not a workstream inside the engineer team—its core to it. You will create and own the AI architecture and best practices the rest of the company utilizes. You will also own the initiatives that put agents into production. You should know how to build and fine-tune foundation models from the ground up, how to engineer best-in-class harnesses, and how to create best practices for agentic engineering that engineering teams adopt to 10x their productivity—without sacrificing quality. Your mindset will be that of a builder and an architect, someone who solves problems in the system itself. No problem will be too large or too small for you to solve yourself. You will set the technical direction and hold the cadenced meetings that turns technical strategy into working, production-ready outcomes. You will be in the design reviews and in the code, not adjacent to them. You will move fast, and you will ensure our engineering team is never the reason an initiative slows down. You are the technical owner of all Toptal’s products. You will collaborate closely with Product to design infrastructure that exposes Toptal’s core business logic through modular interfaces the rest of the business can build on. Alongside a group of hands-on executives, your engineering discipline directly shapes Toptal’s growth, profitability, and operational excellence. You will own resourcing and workforce planning as a doer: scoping the work, sizing the teams, planning headcount against it, defining the role and the bar for every seat. None of that is beneath the role, and we are not interested in someone who thinks these tasks can be done properly by handing it off to HR. Hiring is the highest-leverage work you do, and we want someone who is visibly excited about hiring A-players—with a sense of urgency. Then, you lead the team. You will set the standards, develop people against those standards, and know exactly who is meeting those standards. You will be one of Toptal’s foremost experts on AI, and you will stay ahead of a field that never stops moving. You will coach engineers on agentic best practices, show the executive team what is newly possible with the new AI tooling, and push AI into every function at Toptal. This role runs on high-energy execution and attention to detail. You will bring urgency to every part of it and measure yourself on outcomes. We are not looking for someone to oversee this work. We are looking for someone to drive it and get into the detiwls. This is a remote position. Resumes and communication must be submitted in English. Responsibilities: The following information is intended to describe the general nature and level of work being performed. It is not intended to be an exhaustive list of all duties, responsibilities, or required skills. One precondition runs through all of it: you conceive the strategy. You will form your own view of where engineering and AI should go, build the case, and bring the CEO a strategy to react to, not a request for direction. AI and agentic engineering • Own Toptal’s AI technology strategy and the architecture beneath it: model selection and fine-tuning, harness design, orchestration, retrieval, context engineering, tool and MCP integration, guardrails, evaluation, and cost control, exposed as primitives every team composes against. • Deploy agentic engineering at scale against the work that runs this business: matching, vetting, onboarding, delivery, and internal operations. Own the outcomes those agents are accountable for. • Make AI quality measurable. Own the evals, the regression suites, and the review loops, so quality here is proven rather than claimed. • Rebuild how the platform gets built and operated, raising output per engineer through AI-assisted development, review, testing, and operations. Engineers have to want this, not comply with it, and creating that pull is on you. Team, resourcing, and accountability • Decide what a team should look like now that the roles have blurred, where the product manager believes they can design and code, the engineer believes they can do product and design, and the designer believes they can code and do product. • Own …

Germany | Remote | Full-time | Permanent Employment Our client is a Swiss technology company developing an AI-powered industrial monitoring solution that combines thermal imaging hardware and software. The technology helps industrial facilities prevent fires, identify equipment issues early, and reduce costly unplanned downtime. The company is expanding in Germany and is looking for a Sales Development Representative to build outbound pipeline and open conversations with new industrial customers. This is a phone-first outbound role. You’ll spend much of your time speaking with plant managers, maintenance and reliability leaders, safety teams, operations leaders, and other decision-makers. Experience in industrial technology, manufacturing, or another B2B environment is a plus, but not required. What you’ll do • Build outbound pipeline through cold calling, supported by email and LinkedIn • Research target companies, identify the right contacts, and map accounts • Start conversations with industrial prospects and qualify genuine opportunities • Understand the prospect’s pain, urgency, and decision-making process before handing opportunities to Account Executives • Work attendee lists before trade shows and follow up with prospects afterwards • Identify opportunities across additional facilities and sister sites within existing customer groups • Keep prospecting activity and pipeline data organized in HubSpot • Use modern sales and AI tools to speed up research, preparation, and outreach • Help develop the outbound playbook by documenting approaches, messaging, and objections that work What we’re looking for • Strong cold-calling and communication skills • A proactive, hunter mentality — comfortable creating opportunities rather than waiting for inbound leads • Experience with outbound prospecting, sales development, inside sales, or another call-heavy role • Strong technology literacy and confidence working with CRM, sequencing, prospecting, and AI tools • Ability to research accounts and identify relevant stakeholders rather than simply work through contact lists • Good qualification skills and a disciplined approach to handing opportunities to Account Executives • Resilience, curiosity, coachability, and comfort working in a fast-moving environment • Strong organizational skills and CRM discipline • Fluent German and strong English Experience prospecting into industrial technology, manufacturing, wood processing, recycling, paper, fire protection, industrial automation, predictive maintenance, or similar environments would be a strong advantage. The company is also open to candidates from SaaS or other high-volume outbound environments who can demonstrate strong phone skills and the ability to generate qualified pipeline. What the company offers • Competitive base salary plus uncapped variable compensation tied to qualified meetings and pipeline • A clear opportunity to progress from SDR into an Account Executive / closing role • Direct exposure to company leadership and an experienced commercial team • Modern sales stack and extensive use of AI and automation • High ownership and the opportunity to help shape the company's outbound sales approach in Germany • Flexible remote working model • Occasional participation in trade shows, company events, and customer site visits, with business travel covered Hiring process • Introductory interview • Deep-dive interview focused on your outbound and prospecting experience • Team interview • Cold-call role-play based on a real customer scenario • Final conversation with company leadership • Offer

Germany | Remote / Field-Based | Full-time | Permanent Our client is a Swiss technology company developing an AI-powered industrial monitoring solution that combines thermal imaging hardware and software. The technology helps industrial facilities prevent fires, detect equipment issues early, and reduce costly unplanned downtime. As the company continues to expand across the DACH market, our client is looking for an experienced Account Executive to join the team in Germany. This is a hands-on sales and account development role for someone who can build their own pipeline, win new industrial customers, and grow those relationships over time — from an initial deployment at one facility to broader, multi-site partnerships. The role is remote and field-based, combining home-based work with regular customer site visits across Germany. What you'll do • Own the full sales cycle — from prospecting and discovery to site visits, proposals, negotiation, and closing • Build your own pipeline and actively develop new business • Sell to industrial customers, working with Plant Managers, Operations, Maintenance & Reliability, Safety, Procurement, and executive stakeholders • Own your accounts after the initial sale and grow them over time • Expand successful deployments from one area to the whole facility and across multiple customer sites • Build strong business cases around fire prevention, equipment reliability, downtime, and ROI • Maintain accurate CRM, forecasting, and account plans • Regularly visit customer sites and attend relevant industry events What we're looking for • Proven experience in complex B2B sales of technical or industrial solutions • Experience selling directly to factories, plants, or other industrial facilities • Strong new business / hunter skills and experience generating your own pipeline • Strong account development experience — upselling, expansion, or multi-site growth • Experience working with operational and technical decision-makers • Comfortable with regular travel and face-to-face customer meetings • Based in Germany • Fluent German, with proven experience selling in the German market Experience in industrial automation, fire protection, condition monitoring, predictive maintenance, industrial IoT, machine vision, or safety technology would be highly relevant. What’s offered • Permanent full-time employment • Remote setup with regular customer-facing field work • Competitive base salary + uncapped variable compensation • Commission on both new business and account expansion • Equity • Direct access to company leadership and significant ownership of your accounts • Opportunity to join the commercial team at an early stage of its growth in Germany

Xebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions. We specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture. In the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing. You will be: • prepare and execute test cases for backend and integration scenarios, • perform API testing, including file generation, event flows and Bulk API round-trips, • test integrations between Salesforce and other backend systems, • validate integrations with SEDA, Elliot and an AKS-based integration system, • prepare and maintain test data, • support test environment maintenance and troubleshooting, • analyze test results and report defects, • collaborate with developers, business analysts and other QA engineers in a distributed team. Your profile: • hands-on experience in backend, API or integration testing, • practical experience with API testing and integration test scenarios, • experience preparing test cases and maintaining test data, • understanding of backend event flows and system integrations, • experience testing integrations with Salesforce or similar enterprise platforms, • good understanding of QA processes and testing methodologies, • ability to investigate issues across integrated systems and communicate findings clearly, • Italian at B2+ level , • good English communication skills, • willingness to work from Milan 2–3 days per quarter . Nice to have: • experience with Salesforce integrations, • experience with Bulk API or similar APIs, • familiarity with SEDA, • familiarity with Elliot, • experience with AKS or other Kubernetes-based integration environments. Recruitment Process: CV review – HR call – Interview – Client Interview – Decision