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# Senior AI/ML Engineer

- **Company:** Vizient, Inc.
- **Location:** Chicago, IL, United States
- **Experience:** Expert
- **Salary:** $102,400.0 - $179,000.0
- **Contract:** Permanent contract
- **Skills:** AI Evaluation, Application Programming Interfaces (APIs), Artificial Intelligence, Business Logic, Application Services, Automated Storage and Retrieval Systems, Automation of Tests, Microsoft Azure, Cloud Computing, Code Review, Software Debugging, Information Retrieval, Python (Programming Language), Machine Learning, NoSQL, Open Source Technology, Performance Tuning, Software Maintenance, Regression Testing, Search Technologies, Software Deployment, SQL Databases, Unstructured Data, Workflow Management Systems, Enterprise Search, Enterprise Data Management, Azure Service Bus, Datadog, Enterprise Software Applications, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Model Validation, Software Application Programming, Generative AI, Fastapi, AI Platforms, Data Analytics, Invoking Functions, Databricks
- **Published:** October 31, 2026
- **Apply:** https://diversityjobs.com/career/18796701/Senior-Ai-Ml-Engineer-Illinois-Chicago

## About the Role

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

## Description

In this role, you will design, build, deploy, and support production AI capabilities for complex enterprise workflows. You will 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. You will partner with domain experts, architects, data teams, and software engineers to translate specialized knowledge into maintainable solutions while establishing the evaluation, testing, and observability practices needed to operate AI applications within measurable quality boundaries., * 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.