SQM Infrastructure Product Development AI Engineer

About the role

AI Engineer - Generative AI & Product Engineering

Role Overview

We are seeking a hands-on AI Engineer with strong product development experience to design, build, and deploy enterprise-grade Generative AI solutions. The ideal candidate combines expertise in LLMs, RAG, agentic AI, Python, Azure, and cloud-native engineering with a product mindset focused on scalability, reliability, security, and user experience.

The engineer will work across the full product lifecycle, from architecture and prototyping through API development, deployment, evaluation, monitoring, and production support.

Key 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 Retrieval-Augmented Generation (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 for measuring AI response quality, latency, reliability, and retrieval effectiveness.
• Use LangSmith for tracing, evaluation, debugging, and observability of LLM/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 closely with product owners, architects, and engineering teams to convert business requirements into scalable AI product capabilities.
• Participate in architecture/design reviews, code reviews, testing, deployment, troubleshooting, and ongoing product enhancement.
• Evaluate emerging LLM, retrieval, agentic AI, and AI engineering techniques and apply them where 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.

Required Technical Skills

Generative AI

• Large Language Models (LLMs)
• Azure OpenAI
• Retrieval-Augmented Generation (RAG)
• Prompt Engineering
• Agentic AI / AI Agents
• LLM evaluation and observability

AI Frameworks

• LangChain
• LangGraph
• LangSmith

Application Engineering

• Python
• FastAPI
• REST APIs
• Async/API development
• Microservices architecture

Data & Vector Search

• PostgreSQL
• pgvector
• Vector embeddings
• Semantic/vector search
• RAG retrieval and indexing patterns

Cloud & Deployment

• Microsoft Azure
• Azure Kubernetes Service (AKS)
• Containers/Docker
• Cloud-native application development
• CI/CD and production deployment practices

Product Development Experience

The candidate should demonstrate experience taking AI capabilities beyond proof-of-concept into production products, including:

• Translating business requirements into technical product capabilities
• Designing reusable and maintainable AI architectures
• Balancing model quality, latency, cost, security, and scalability
• Designing APIs and integration patterns for enterprise applications
• Establishing AI evaluation and quality measures
• Troubleshooting production LLM/RAG applications
• Collaborating across engineering, architecture, product, QA, DevOps, and business teams
• Owning features through design, development, testing, deployment, and production stabilization

Preferred Qualifications

• 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 is a plus.

Salary Range

$80,800 - 133,400 USD

Salary range is a good faith estimate of base pay. Northern Trust provides a comprehensive benefits package including retirement benefits (401k and pension), health and welfare benefits (medical, dental, vision, spending accounts and disability), paid time off, parental and caregiver leave, life & accident insurance, and other voluntary and well-being benefits. Northern Trust also provides a discretionary bonus program that may include an equity component.

Work Authorization

Applicants must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future. Northern Trust will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT or any other employment-based visa).

Working with Us

As a Northern Trust partner, you will be part of a flexible and collaborative work culture, which has a strong history of financial strength and stability. Movement within the organization is encouraged, senior leaders are accessible, and you can take pride in working for a company committed to an inclusive workplace and assisting the communities we serve.

Philanthropy is deeply rooted in Northern Trust's history and is an essential element of our culture. Employees around the world give their time and talent to work for the greater good of their communities.