AI Systems Engineer - Agents & Inference

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 $370 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 …