SQM Infrastructure Product Development AI Engineer

Northern Trust • Chicago, IL

10d

About The Position

Northern Trust is seeking a hands-on AI Engineer with product development experience to design, build, and deploy enterprise-grade generative AI solutions. The role combines expertise in large language models, retrieval-augmented generation (RAG), agentic AI, Python, Azure, and cloud-native engineering, with a product focus on scalability, reliability, security, and user experience.

The engineer will contribute throughout the product lifecycle, from architecture and prototyping to API development, deployment, evaluation, monitoring, and production support. They will work with product owners, architects, engineering teams, and partners across application, infrastructure, cloud, database, and operations to translate business needs into scalable AI capabilities, resolve production issues, and enhance products over time.

Requirements

• Demonstrated product development experience taking AI capabilities beyond proof of concept into production products.
• Experience translating business requirements into technical product capabilities.
• Ability to design reusable and maintainable AI architectures.
• Ability to balance model quality, latency, cost, security, and scalability.
• Experience designing APIs and integration patterns for enterprise applications.
• Experience establishing AI evaluation and quality measures.
• Experience troubleshooting production LLM and RAG applications.
• Experience collaborating across engineering, architecture, product, QA, DevOps, and business teams.
• Generative AI and large language model experience.
• Experience with Azure OpenAI, RAG, prompt engineering, agentic AI or AI agents, and LLM evaluation and observability.
• Experience with LangChain, LangGraph, and LangSmith.
• Experience with Python, FastAPI, REST APIs, asynchronous/API development, and microservices architecture.
• Experience with PostgreSQL, pgvector, vector embeddings, semantic/vector search, and RAG retrieval and indexing patterns.
• Experience with Microsoft Azure, Azure Kubernetes Service (AKS), containers/Docker, cloud-native application development, CI/CD, and production deployment practices.

Nice To Haves

• Strong hands-on experience developing enterprise GenAI/RAG products.
• Experience building LangGraph-based agentic workflows.
• Hands-on experience with LangSmith tracing and evaluation.
• Experience deploying Python/FastAPI applications on AKS.
• Experience with PostgreSQL/pgvector at production scale.
• Understanding of LLM hallucination, grounding, context management, guardrails, and evaluation.
• Familiarity with Azure identity, secrets management, monitoring, and enterprise security patterns.
• Experience building internal developer, infrastructure, automation, operations, or knowledge-management AI products.

Responsibilities

• Design and develop enterprise generative AI and agentic AI applications using LangChain, LangSmith, and LangGraph.
• Build multi-step and stateful AI workflows involving reasoning, tool integration, retrieval, and human-in-the-loop patterns.
• Develop RAG solutions using PostgreSQL and pgvector for vector storage and semantic retrieval.
• Integrate applications with Azure OpenAI and other LLM-based services.
• Design effective prompts and reusable prompt patterns using advanced prompt-engineering techniques.
• Build scalable backend services and REST APIs using Python and FastAPI.
• Develop evaluation and observability mechanisms to measure AI response quality, latency, reliability, and retrieval effectiveness.
• Use LangSmith to trace, evaluate, debug, and observe LLM and agent workflows.
• Containerize and deploy AI services to Azure Kubernetes Service (AKS).
• Design solutions using appropriate Azure services for identity, security, networking, storage, monitoring, and application integration.
• Implement production-ready practices, including exception handling, logging, retries, API security, configuration management, and observability.
• Work with product owners, architects, and engineering teams to convert business requirements into scalable AI product capabilities.
• Participate in architecture and design reviews, code reviews, testing, deployment, troubleshooting, and ongoing product enhancement.
• Evaluate emerging LLM, retrieval, agentic AI, and AI engineering techniques and apply them when they provide measurable product value.
• Partner with application, infrastructure, cloud, database, and operations teams during major incidents and production issues to identify dependencies and resolve problems.
• Own AI product features through design, development, testing, deployment, and production stabilization.

Benefits

• Retirement benefits, including 401(k) and pension.
• Health and welfare benefits, including medical, dental, vision, spending accounts, and disability benefits.
• Paid time off.
• Parental and caregiver leave.
• Life and accident insurance.
• Other voluntary and well-being benefits.
• Discretionary bonus program that may include an equity component.

What This Job Offers

• Job Type: Full-time
• Education Level: No Education Listed