Senior Agentic AI Engineer NDA

GT was founded in 2019 by a former Apple, Nest, and Google executive.  GT’s mission is to connect the world’s best talent with product careers offered by high-growth companies in the UK, USA, Canada, Germany, and the Netherlands.

On behalf of the client, GT is looking for a Senior Agentic AI Engineer who is interested in solving complex matching and search problems at scale, applying ML and algorithms to hundreds of millions of real-world data records.

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About the Client

Our client is a leading global management consultancy known for tackling some of the world’s most complex business challenges. With a focus on strategy, transformation, and performance improvement, the firm partners with major organizations across industries to drive lasting impact.

Recognized consistently as a top workplace, it combines deep industry expertise with a collaborative, innovative culture. Its centralized European hub plays a key role in supporting operations across the EMEA region, ensuring excellence and efficiency at scale.

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About the Project & Role

We are looking for a Senior AI Engineer to help design, build, and evolve an AI-powered conversational analytics platform that enables businesses to explore their data, generate insights and visualizations, and make data-driven decisions.

The product helps users analyze promotional performance, answer complex analytical questions, build charts and tables, and generate evidence-based recommendations using LLMs, agentic workflows, and governed client data.

The team is developing a scalable, secure, and extensible agentic AI framework that can be customized for different clients and integrated with other products through standards such as Model Context Protocol (MCP). The existing solution is built on LangChain, with plans to evolve and migrate the framework.

This is a hands-on engineering role with a significant architecture and system design component. You will work across the entire agentic AI lifecycle, from designing agent workflows, tools, and integrations to implementing evaluation frameworks, improving reliability, and delivering production-ready AI features.

Responsibilities

• Design, build, and evolve agentic AI workflows for data exploration, analysis, and conversational insights.
• Develop and improve an extensible agentic framework , including orchestration, reusable tools, skills, and conversation management.
• Build secure integrations with application services and governed data sources, including sandboxed code execution and AI-powered data visualizations.
• Design configurable solutions supporting client-specific prompts, tools, skills, and data definitions without duplicating the core architecture.
• Develop MCP servers and clients to enable communication and data exchange between agents and applications.
• Contribute to architectural decisions and the evolution and migration of the existing LangChain-based solution .
• Implement LLM evaluation, testing, observability, and security controls to ensure accurate, reliable, and data-grounded AI outputs.
• Own features end to end, from technical design and implementation to production release and continuous improvement, collaborating with cross-functional teams.

Essential Knowledge, Skills & Experience

Core Requirements

• 6+ years of experience in software engineering, data analytics, or related fields, including 2+ years in agentic AI engineering .
• Strong Python development skills, with experience building, testing, and maintaining production-grade applications.
• Hands-on experience building agentic AI systems using frameworks such as Pydantic AI, LangGraph, LangChain, or OpenAI Agents SDK.
• Strong understanding of agentic patterns, including tool calling, multi-step orchestration, context management, guardrails, and human-in-the-loop workflows.
• Experience with MCP (Model Context Protocol) and multi-agent or cross-application integrations.
• Experience developing AI agents for data analysis, including dataset exploration, code generation and execution, and result interpretation.
• Strong system design and architecture skills, including building configurable, extensible solutions and evaluating technical trade-offs.
• Understanding of AI security, evaluation, and observability, including secure data access, LLM testing, tracing, and performance monitoring.
• Strong ownership, communication, and cross-functional collaboration skills, with practical experience using AI coding assistants (Claude Code, Codex, or similar).

Strongly Preferred

• Experience with Pydantic AI / Pydantic AI Harness and LangChain , particularly migration between frameworks.
• Familiarity with SQL, pandas, DuckDB, or Ibis for data analysis.
• Experience with Azure OpenAI, Docker, and analytical visualization tools such as Plotly or Dash.

Nice-to-Have

• Experience with retail, pricing, promotions analytics, or similar domains.
• Experience delivering client-facing AI products from prototype to …