Senior AI/ML Engineer

Vizient•Chicago, IL

About The Position

Design, build, deploy, and support production AI capabilities for complex enterprise workflows. Develop AI-enabled applications that combine large language models, retrieval, structured and unstructured data, deterministic processing, APIs, and distributed services to produce reliable and explainable results. Partner with domain experts, architects, data teams, and software engineers to translate specialized knowledge into maintainable solutions, and establish evaluation, testing, and observability practices to operate AI applications within measurable quality boundaries. The role supports deployed AI applications through monitoring, troubleshooting, performance optimization, and production issue resolution, while contributing reusable AI engineering patterns, components, documentation, and evaluation practices.

Requirements

Five or more years of relevant experience.
Strong experience developing production applications using Python.
Hands-on experience building, deploying, and supporting generative AI or machine learning applications in production environments.
Experience integrating commercial or open-source large language models through APIs or managed AI platforms.
Experience with prompt engineering, structured model outputs, tool or function calling, retrieval-augmented generation, or agentic workflows.
Experience building data-driven APIs and distributed application services using FastAPI or comparable frameworks.
Experience developing automated tests and evaluation methods for nondeterministic AI behavior.
Experience with embeddings, semantic search, vector retrieval, reranking, or comparable knowledge-retrieval techniques.
Experience with cloud-native development, CI/CD pipelines, containerized services, and production deployment.
Experience debugging complex issues across application code, enterprise data, AI models, retrieval systems, and distributed workflows.

Nice To Haves

Relevant degree preferred.
Experience with Microsoft Azure, Azure AI Foundry, Azure AI Search, Databricks, or Azure Service Bus.
Experience with AI evaluation, tracing, observability tooling, SQL, NoSQL databases, or agent-orchestration frameworks.
Experience developing applications involving sensitive, regulated, or high-consequence enterprise data.

Responsibilities

Design and implement production AI-enabled application services and workflow components.
Build modular large language model and agentic capabilities with clearly defined responsibilities, inputs, outputs, and evaluation criteria.
Develop retrieval and grounding solutions using structured data, semantic search, vector retrieval, and enterprise knowledge sources.
Combine deterministic processing, business rules, retrieval, and model-based inference appropriately within application workflows.
Build APIs, services, orchestration components, and asynchronous processing capabilities for production AI workloads.
Develop automated evaluation and regression testing for large language model and AI behavior.
Instrument applications to trace inputs, intermediate results, model interactions, decisions, errors, latency, and operational behavior.
Investigate AI failure modes and use evaluation evidence to improve prompts, retrieval, workflow design, model selection, and application logic.
Evaluate models and implementation approaches based on measurable quality, performance, security, maintainability, and cost.
Implement controls that validate, constrain, and monitor model outputs within enterprise applications.
Collaborate with domain experts to translate complex decision processes into maintainable software behavior.
Participate in architecture reviews, technical design sessions, code reviews, and continuous improvement activities.
Develop reusable AI engineering patterns, components, documentation, and evaluation practices.
Support deployed AI applications through monitoring, troubleshooting, performance optimization, and production issue resolution.