Manager AI Software Engineering

Role overview

AI development and delivery

• Build and iterate agents using Microsoft Foundry and implement Python LLM patterns such as RAG, tool use, structured outputs, memory, and multi-agent orchestration.
• Integrate with Palantir Foundry through MCP to access enterprise data and carry out ontology-driven actions.
• Translate product requirements into scalable designs; deploy with CI/CD and automated evaluation release gates.
• Version code, prompts, tools, and configurations; optimize architecture for performance, cost, and latency.

Operations and platform integration

• Operate production agents with observability, tracing, cost monitoring, regression tests, and incident response; address reliability, latency, cost, and quality issues.
• Secure enterprise data using authentication, authorization, and secret management with Azure services.
• Integrate with Azure OpenAI, AI Search, Storage, Functions, Container Apps, and identity services.
• Build scalable agent architecture patterns and contribute reusable components, libraries, and shared engineering practices.

Evaluation and collaboration

• Create evaluation harnesses and guardrails for groundedness, safety, latency, and cost, then iterate using measured outcomes and user feedback.
• Work in agile squads with Product Managers, Data Scientists, and Architects to take use cases from prototype to production.
• Explain technical trade-offs and support alignment between engineering delivery and product priorities.

Experience and education

• At least two years of experience deploying agentic AI systems and production software engineering experience building LLM-based or agentic systems.
• Bachelor’s degree in computer science, engineering, or a related quantitative field; advanced degrees are preferred.

Technical competencies

• Strong Python skills, including typed and tested code, async, and modern packaging.
• Production AI agent framework experience such as Microsoft Foundry, Semantic Kernel, AutoGen, LangGraph, LlamaIndex, OpenAI Agents SDK, or an equivalent custom framework.
• Microsoft Foundry experience is strongly preferred; Azure exposure includes Azure OpenAI, AI Search, identity, storage, and serverless compute.
• Knowledge of tool/function calling, structured outputs, RAG, memory, and multi-agent orchestration; LLM evaluation and observability experience.
• DevOps fundamentals include Git, CI/CD, containers, and infrastructure as code. Data engineering and vector store exposure is a plus.

Behavioral competencies

• Ownership, accountability, structured problem-solving, and analytical capability.
• Ability to collaborate across delivery teams and communicate technical concepts and trade-offs clearly.
• Adaptability in fast-paced and evolving delivery environments.

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