What are the responsibilities and job description for the Generative AI Engineer position at Robert Half?
The Opportunity
While 2024 was the year of AI experimentation, 2026 is the year of Agentic AI. Our client, a Financial Services leader in Fulton Market, is moving beyond simple chatbots to build autonomous AI agents capable of multi-step reasoning and enterprise-scale task execution.
We are looking for an AI Engineer who doesn't just "call an API" but understands how to build resilient, cost-effective, and secure production systems. You will be joining a high-priority squad tasked with automating core business logic using the latest LLM orchestration frameworks.
Key Responsibilities
- Agent Orchestration: Design and deploy multi-agent systems using frameworks like LangGraph, CrewAI, or PydanticAI to handle complex, non-linear workflows.
- Advanced RAG Pipelines: Implement and optimize Retrieval-Augmented Generation (RAG) using vector databases (Pinecone, Weaviate, or Milvus) and advanced reranking strategies.
- Model Optimization: Fine-tune open-source models (Llama 3/4, Mistral) using LoRA/QLoRA for domain-specific tasks while maintaining low latency.
- AI FinOps & Guardrails: Implement token-cost monitoring and security guardrails (Zero Trust integration) to ensure LLM outputs are safe, compliant, and within budget.
- Production Engineering: Containerize AI microservices using Docker/Kubernetes and set up CI/CD pipelines for model deployment and monitoring (MLOps).
Technical Requirements
- Python Mastery: 5 years of Python development (including experience with Python 3.12 features).
- LLM Experience: Proven track record of shipping LLM-powered applications to production (OpenAI, Claude, or local hosting).
- Data Architecture: Strong SQL skills and experience with unstructured data processing.
- Chicago Connection: Must be able to commute to the Chicago office 3 days a week to collaborate with the engineering leadership team.
Salary : $167,500 - $233,500