Senior Agentic AI Engineer | NDA

Gt Hq | Management Consulting

3h 16m ago

On-site

Full Time

Poland

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 AI outputs that reconcile with governed application data.
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.
Practical experience with LLM evaluation, testing, and observability (Phoenix, OpenTelemetry, or similar), including tracing, quality metrics, and regression testing, alongside an understanding of AI security and secure data access.
Strong ownership, communication, and collaboration skills, with effective daily use of AI coding assistants (Claude Code, Codex, or similar) and validation of generated code.

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.

Required Skills

pythonlangchainlanggraph

Required Languages

🇬🇧 English

About the Client

About the Project & Role

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 AI outputs that reconcile with governed application data.

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.

Practical experience with LLM evaluation, testing, and observability (Phoenix, OpenTelemetry, or similar), including tracing, quality metrics, and regression testing, alongside an understanding of AI security and secure data access.

Strong ownership, communication, and collaboration skills, with effective daily use of AI coding assistants (Claude Code, Codex, or similar) and validation of generated code.

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.

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.