Artificial Intelligence Engineer

Location:

Downtown Chicago at least 2wks per month and Atlanta or NYC may be acceptable.

Over 10+ Years of IT Experience.

Key Role Activities

• Design and build agentic systems for multi-step reasoning, planning, tool use, and workflow execution in regulated processes.
• Build stateful workflows with LangGraph/LangChain — branching, retries, self-correction, human-in-the-loop checkpoints.
• Engineer for reliability: error recovery, planning under uncertainty, robust handling of failed tool calls.
• Build auditable, policy-grounded reasoning for high-stakes decisions (e.g., prior authorization, claims review).
• Build RAG pipelines: ingestion, chunking, embeddings, retrieval, reranking, grounding.
• Manage conversational state, persistent memory, and context assembly; apply MCP-style tool/context interfaces.
• Implement observability and tracing (Azure Monitor/Application Insights) for prompts, tool calls, and agent behavior.
• Apply guardrails to reduce hallucinations and unsafe actions; evaluate agents at the task and trajectory level.
• Support PHI/HIPAA-aware data handling and human-oversight/escalation for regulated decisions.
• Integrate agents with enterprise systems and APIs (e.g., MuleSoft as an integration layer).
• Deploy and operate on Azure — AKS/ARO, Key Vault, Redis, Kafka, Istio, networking.
• Deliver production-quality code with strong testing, CI/CD, and documentation practices.

Required Qualifications

• Demonstrated production experience building agentic systems, not just exploration.
• Hands-on experience with LangGraph/LangChain or equivalent orchestration.
• Experience building end-to-end RAG systems: indexing, retrieval, reranking, grounding, evaluation.
• Solid understanding of context/memory management and retrieval-driven context assembly.
• Practical understanding of LLM limitations, hallucination risks, and evaluation methods.
• Experience debugging agent behavior at the trajectory/task level.
• Strong Python skills: testing, CI/CD, version control, API integration, production observability.
• Hands-on experience with at least one frontier model platform (Anthropic, Google, OpenAI).
• Working knowledge of Azure infrastructure — AKS/ARO, Key Vault, Redis, Kafka, Istio, networking.
• Clear communication and problem solving skills, ability to meet deadlines, plan work and pivot as needed, and work with a multidisciplinary, diverse team.
• Ability to travel 0–50% as needed.