Senior AI/ML Team Lead – Enterprise GenAI Architect

Vizient, Inc.; Chicago (IL); On-site; USD 118,000 - 206,000; Full time

Job summary

Vizient, Inc. is seeking an experienced AI and ML systems leader to design, deploy, and operate enterprise-grade AI solutions for complex workflows.

You will work hands-on with architecture and implementation while guiding engineers and collaborating with domain experts, product, data, and platform teams. The role emphasizes responsible AI, observability, security, and scalable patterns across Azure, Databricks, and semantic retrieval.

Qualifications

• Relevant degree preferred.
• 7+ years of relevant experience required.
• Experience providing technical leadership for complex, production-grade software or AI systems.
• Hands-on design, build, deploy, and operate generative AI in enterprise environments.
• Strong Python experience and API/service development (FastAPI or similar).
• Experience with LLMs, prompt engineering and retrieval-augmented generation.
• Define evaluation strategies: test data, regression, grounding, quality metrics.
• Balance probabilistic AI with deterministic software, rules and data processing.
• Cloud-native architecture, async processing, APIs, queues, observability.
• Address security, privacy, reliability, auditability, cost requirements.
• Azure/Azure AI Foundry/Search preferred.
• Databricks, vector DBs, embeddings, semantic search preferred.
• Handling sensitive or high-consequence data experience preferred.
• Strong leadership, mentoring, communication, problem solving, architecture and collaboration skills.

Responsibilities

• Lead the architecture, development, deployment, and operation of enterprise-grade AI and ML solutions.
• Design solutions combining LLMs, agentic workflows, retrieval, structured data, APIs, and deterministic processing.
• Translate complex expert workflows into modular, testable software components.
• Determine where AI inference, deterministic logic, retrieval, rules, or data processing will produce the most reliable outcome.
• Establish evaluation strategies with test sets, expert-reviewed outcomes, regression testing, quality measurements, and stage-level analysis.
• Design observability capabilities that capture intermediate outputs, decision traces, evaluation results, performance measures, and failure modes.
• Lead investigations into grounding failures, hallucinations, retrieval quality, prompt behavior, model selection, orchestration, latency, accuracy, and cost.
• Evaluate architectural tradeoffs across performance, maintainability, security, reliability, supportability, and operating cost.
• Develop APIs, services, prototypes, and production components while contributing to design reviews, code reviews, and complex technical problem-solving.
• Implement security, privacy, auditability, monitoring, and production-readiness practices for AI-enabled applications.
• Partner with domain experts, product leaders, architects, data teams, and platform teams to convert specialized knowledge into scalable system behavior.
• Develop reusable AI capabilities, engineering patterns, evaluation frameworks, and platform components that support multiple solutions.
• Mentor engineers and strengthen team practices across AI engineering, software design, testing, observability, and production operations.
• Drive continuous improvement by incorporating production metrics, evaluation results, expert feedback, and real-world user outcomes.

Skills

Technical leadership

Mentoring

Communication

Problem-solving

Architecture

Cross-functional collaboration

Education

Relevant degree preferred

Tools

Python

FastAPI

Job description

Vizient, Inc. is seeking an experienced AI and ML systems leader to design, deploy, and operate enterprise-grade AI solutions for complex workflows.

You will work hands-on with architecture and implementation while guiding engineers and collaborating with domain experts, product, data, and platform teams. The role emphasizes responsible AI, observability, security, and scalable patterns across Azure, Databricks, and semantic retrieval.