Sr.Associate - GenAI Engineer

About Northern Trust As a global leader in innovative wealth management, asset servicing, asset management and banking services, Northern Trust (Nasdaq: NTRS) is proud to guide the world’s most successful individuals, families, corporations and institutions. Since 1889, we have aligned our efforts with our three guiding Principles That Endure: Service, Expertise, and Integrity. Together, they reflect the three cornerstones of business conduct which we strive to instill in our employees, whom we call partners, and to provide to our clients and the communities we serve worldwide. With more than 135 years of financial experience and over 24,000 partners, we serve the world’s most sophisticated clients using leading technology and exceptional service. Primary Skills: Generative AI, Agentic AI, Python, LangChain/LangGraph Good to Have: Data Science, Machine Learning, MLOps, Statistical Analysis Major duties: Design, develop, test, and maintain enterprise-grade Generative AI and Agentic AI applications. Translate business requirements into scalable AI solutions and contribute to technical roadmaps. Develop proof-of-concepts, feasibility studies, and solution prototypes for AI use cases. Build intelligent agents and multi-agent workflows using Python, LangChain, and LangGraph. Develop reusable AI services, APIs, tools, and orchestration components. Design RAG solutions using structured and unstructured enterprise data. Implement prompt engineering, context management, agent memory, state management, and tool calling. Develop evaluation frameworks covering accuracy, relevance, groundedness, safety, and agent performance. Ensure AI solutions are modular, scalable, secure, reliable, observable, and maintainable. Integrate AI applications with enterprise systems, databases, knowledge repositories, and CI/CD pipelines. Troubleshoot issues and optimize AI solutions for quality, performance, and cost. Collaborate with cross-functional teams and follow Responsible AI, security, privacy, and governance standards. Knowledge: Strong expertise in Python programming and AI application development. Hands-on experience with Generative AI, Large Language Models, and Agentic AI solutions. Strong working knowledge of LangChain, LangGraph, or similar agent-orchestration frameworks. Good understanding of prompt engineering, context engineering, structured outputs, and function/tool calling. Experience with agent memory, workflow state, session management, checkpointing, and multi-agent orchestration. Strong knowledge of RAG, embeddings, vector databases, semantic search, chunking, retrieval, and reranking techniques. Experience with LLM and agent evaluations, including groundedness, relevance, accuracy, safety, trajectory, and task-completion assessment. Experience developing REST APIs, microservices, and cloud-based applications. Hands-on experience with Git, CI/CD pipelines, automated testing, and DevOps practices.