Lead AI Automation Engineer

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The Lead AI Automation Engineer will provide hands-on technical leadership for the design, engineering, and productionization of AI-enabled automation across the Data Governance organization. This role is focused on building reliable automation products and agentic workflows—not training foundational models or serving as a traditional data scientist. The engineer will combine generative AI, workflow orchestration, APIs, enterprise integrations, low-code automation where appropriate, and production engineering practices to automate complex governance processes.

The role will lead technical design, establish reusable engineering patterns, mentor other engineers, and take high-value automation opportunities from concept through secure, scalable production deployment.

Key Responsibilities Lead the technical design and hands-on development of AI-enabled automations, agentic workflows, and intelligent process orchestration for enterprise Data Governance use cases.

Build solutions that combine large language models, deterministic business logic, workflow engines, APIs, enterprise data, and human-in-the-loop controls.

Design reusable automation frameworks, services, connectors, prompts, tools, and patterns that accelerate delivery across multiple governance workflows.

Integrate AI automation with metadata management, data catalog, data quality, lineage, policy, ticketing, collaboration, and enterprise data platform capabilities.

Engineer APIs and services that allow agents and automations to safely retrieve context, execute approved actions, and interact with enterprise systems.

Use Power Platform and other low-code automation technologies where they are the appropriate engineering choice, while applying software engineering discipline to maintainability, security, testing, and lifecycle management.

Establish patterns for agent orchestration, tool use, state management, exception handling, observability, auditability, human approval, and failure recovery.

Define and implement evaluation, testing, monitoring, and quality controls for AI automations, including accuracy, reliability, latency, cost, and operational performance.

Partner with architects, security, AI/data science teams, product owners, governance leaders, and application teams to translate business processes into secure and scalable automation solutions.

Lead technical reviews, mentor engineers, improve engineering standards, and provide technical direction without becoming removed from hands-on delivery.

Identify processes that are strong candidates for automation and challenge unnecessary manual steps, handoffs, and duplicated workflows.

Own production readiness and operational support, including CI/CD, release management, telemetry, incident troubleshooting, continuous improvement, and responsible AI controls.

Use your skills to make an impact

Required Qualifications Bachelor's degree in Computer Science, Software Engineering, Information Systems, Engineering, Data Science, Artificial Intelligence, or a related technical field; or equivalent combination of education and relevant professional experience.
5+ years of experience in software engineering, application development, automation engineering, platform engineering, or enterprise systems integration.
2+ years of hands-on experience developing AI/ML, generative AI, intelligent automation, or advanced automation solutions, with demonstrated recent experience building LLM-enabled or agentic solutions.

Demonstrated experience taking complex automation or AI-enabled solutions from concept/prototype through production deployment and operational support.

Demonstrated experience providing technical leadership—such as leading solution design, establishing engineering patterns, conducting technical/code reviews, mentoring engineers, or serving as the technical lead for complex initiatives.

Preferred Qualifications Master's degree in Computer Science, Engineering, Artificial Intelligence, Information Systems, Data Science, or a related discipline.
7+ years of overall engineering experience, including experience designing enterprise-scale automation, integration, or AI solutions.

Experience leading AI automation, generative AI, agentic AI, or intelligent process automation initiatives in a large enterprise.

Experience working in a regulated enterprise environment where security, privacy, auditability, governance, and responsible AI controls are material design requirements.

Relevant cloud, AI,…