About this Senior Agentic AI Engineer | NDA role at GT
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 our client, GT is looking for a Senior Agentic AI Engineer to help design and evolve a production-grade AI platform for conversational data analytics. This role combines hands-on Python engineering with architectural decision-making, offering the opportunity to build scalable agentic AI systems, solve complex engineering challenges, and shape how businesses interact with their data through AI.
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.
About the Project & Role
Our client is developing an AI-powered conversational analytics platform that helps businesses explore their data, answer complex analytical questions, generate visualizations, and make evidence-based decisions about promotional performance.
The platform already has an agentic solution built on LangChain, and the team is gradually evolving its architecture around Pydantic AI. The goal is to build a more scalable, secure, and extensible framework that supports client-specific configurations, reliable data analysis, and integration with other products through MCP.
As a Senior Agentic AI Engineer, you'll help shape this evolution, combining hands-on development with architectural contributions. You'll work on real engineering challenges, including secure code execution, agent orchestration, cross-product integrations, and ensuring AI-generated insights are accurate and grounded in trusted data.
You'll collaborate with engineers, product managers, and other stakeholders to develop, evaluate, and deliver AI capabilities that work reliably in production.
Responsibilities
Design, build, and improve agentic AI workflows for conversational analytics, data exploration, and visualization.
Develop an extensible agentic framework with reusable tools, skills, conversation management, and client-specific configurations.
Build secure integrations with application services and governed data sources, including sandboxed code execution.
Contribute to the evolution of the existing LangChain-based solution toward Pydantic AI, evaluating frameworks and making architectural decisions.
Develop MCP servers and clients to enable communication and data exchange between agents and applications.
Implement LLM evaluation, testing, observability, and security controls to ensure reliable, accurate, and data-grounded outputs.
Own AI features end to end, from implementation and testing to production release and continuous improvement, working closely 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 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.
Solid system design and architecture skills, including designing 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 collaboration skills, with practical experience using AI coding assistants (Claude Code, Codex, or similar).
Strongly Preferred
Hands-on experience with Pydantic AI / Pydantic AI Harness, including knowledge of its capabilities and architectural patterns.
Experience designing agentic foundations for software products and/or evolving existing agentic solutions, with the ability to contribute to architectural decisions.
Familiarity with LangChain-based systems, particularly their architecture, limitations, and evolution.
Experience with data analysis technologies such as SQL, pandas, DuckDB, or Ibis.
Familiarity with Azure OpenAI, Docker, and data 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 production.
Familiarity with React and FastAPI.
Interview Process
Interview with GT Recruiter
Cultural Fit Interview
Technical Interview
Final Interview
Offer
Why Join Our Client?
Real product impact: Build AI capabilities used for complex analytical decisions, where reliability and accuracy matter.
Technical influence: Help evolve an existing AI platform and contribute to its architectural direction while remaining hands-on.
Challenging engineering environment: Work on complex problems involving agentic systems, governed data, secure execution, and cross-product integrations.
