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About the role
Description Were looking for a Lead AI Engineer with minimum 10 years of experience who thrives on building production-grade, agentic AI systems that power real business workflows. You have strong Python skills, hands-on experience working with LLMs in production (prompt engineering, tool/function calling, structured outputs and RAG), and working knowledge of LangChain or LangGraph (or a comparable framework such as LlamaIndex, CrewAI or Semantic Kernel). You are comfortable writing solid SQL, working with at least one major cloud, and shipping reliable services using Git, Docker and a modern API framework like FastAPI. As a Lead AI Engineer on the Tech Hub team, you will play a key role in building on that platform shipping agent harnesses, writing the tools those agents call, and owning the reliability and evaluation of what goes to production. This is not a research role : you will prototype, ship, monitor and iterate on features used by real teams, working closely with our U.S. AI & Innovation team and cross-functional partners across Engineering, Data, QA and Product. How You Will Make An Impact Design and build agent harnesses in Python using LangChain and LangGraph, including tool-calling, structured outputs (Pydantic / JSON schema), retries, streaming and memory Package agents as Dataiku Code Agents, custom plugins, and Python / SQL recipes that fit cleanly into production flows and scenarios Write the tools agents use API integrations, SQL queries against Snowflake, and Knowledge Bank retrievals with clear contracts and Pydantic validation Build evaluation harnesses (golden datasets, LLM-as-judge, regression suites) using Dataiku Evaluations, and wire them into CI Implement guardrails around tool execution : auth scoping, input / output validation, PII and prompt-injection protections, and hallucination mitigation Own what you ship prototype, deploy through Dataiku, monitor traces, and fix issues quickly when something breaks in production Partner with data engineers on Snowflake-backed retrieval patterns (Cortex Analyst and Cortex Search Services) and with platform teams on observability, security and cost Help shape internal patterns and AI engineering standards as the stack evolves, contributing to design reviews and sharing knowledge across the India and U.S. teams Participate in a collaborative DevOps environment, working closely with developers, QA, DBAs and product partners across your first 90 days : By the end of your first 90 days, you will have shipped at least one production agent end-to-end such as a retrieval-backed analyst assistant or a workflow automation harness. You will have traces and evaluations running against a golden dataset, a Dataiku plugin or Code Agent registered in the LLM Mesh, and a clear opinion about what our next agent should do. What You Need To Be Successful 3+ years of professional Python experience, with production experience building and operating services 1+ years of hands-on work with LLMs in production : prompt engineering, tool / function calling, structured outputs and RAG Working knowledge of LangChain or LangGraph or a comparable framework like LlamaIndex, CrewAI or Semantic Kernel Solid SQL skills and comfort with at least one cloud platform (AWS, Azure or GCP) Fluency with Git, Docker and a modern API framework like FastAPI Solid understanding of data security and responsible AI practices, particularly in PCI-compliant or regulated environments Proven ability to work independently and within a team, managing priorities across concurrent projects and time zones Strong written and verbal communication skills; able to work effectively with both technical and non-technical stakeholders A bachelors degree is not required equivalent practical experience (including bootcamps, self-taught work, career changes or non-CS technical degrees) counts Bonus Skills Hands-on experience with Dataiku DSS as a coder : Python / SQL recipes, scenarios, managed folders, code environments, the dataiku and dataikuapi clients, webapps or plugin development Experience with Dataiku LLM Mesh, Knowledge Banks, Prompt Studio, or Visual / Code Agents Experience with Snowflake, Snowpark, or Snowflake Cortex (Search, Analyst, Agents) Experience with LLM observability tools : LangSmith, Langfuse, MLflow or OpenTelemetry Experience designing evaluation frameworks (RAGAS, DeepEval, LLM-as-judge, multi-turn regression) Familiarity with multi-agent patterns : supervisor / router, subagent / handoff, reflection, human-in-the-loop A Dataiku Developer or Advanced Designer certification Experience in loyalty, martech, adtech or a comparable data-rich B2B domain (ref:hirist.tech)