AI Technical Lead

Job Description

Job Description

Information Technology / Operations

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The AI Technical Lead helps turn approved AI opportunities into practical, secure, and measurable business solutions.
This role evaluates use cases, shapes solution architecture, guides prototypes, coordinates delivery, and prepares AI capabilities for operational use while partnering with IT and governance and control functions on policy, approval, and risk decisions.

• Lead AI intake discussions, clarify business needs, and define expected outcomes and success measures.
• Evaluate priority workflows for business value, feasibility, data readiness, integration needs, complexity, and supportability.
• Design AI solution approaches, reusable patterns, integrations, human review points, and operating requirements.
• Evaluate AI platforms, models, vendors, and products, including security and third-party risk considerations.
• Build or guide proofs of concept and validate accuracy, reliability, usability, cost, and technical fit.
• Coordinate development, testing, deployment readiness, access, support, release activities, and operational monitoring.
• Support governance reviews with recommendations, evidence, status updates, and escalation of material technical risks.
• Maintain the AI roadmap and backlog, align delivery priorities, and help teams use approved AI capabilities effectively.

• 7+ years in technology leadership, software delivery, technical program management, enterprise architecture, data science, or a related field.
• 3+ years delivering or evaluating enterprise AI, machine learning, analytics, or LLM-enabled solutions.
• Proficiency in Python and SQL, with experience using cloud AI services, LLM platforms, APIs, integrations, solution architecture, and AI delivery data patterns.
• Experience moving solutions from feasibility assessment and proof of concept through testing, implementation, monitoring, and support.
• Ability to work across multiple business units, IT, cybersecurity, data governance, privacy, legal, vendor, and governance teams while explaining technical decisions clearly.
• Bachelor’s degree in Computer Science, Engineering, Data Science, Data Analytics, Information Technology, or a related field.

• Master’s degree in a relevant technical or analytical field.
• Experience with Azure AI, Microsoft Copilot, Azure OpenAI, or similar enterprise AI platforms.
• Experience with MLOps or LLMOps, including evaluation, observability, reliability, lifecycle management, and cost control.
• Working knowledge of responsible AI, NIST AI RMF, privacy, security, and enterprise risk processes.

Success in this role means AI opportunities are assessed consistently, high-impact workflows are prototyped and validated, and approved solutions move through a disciplined path from prototype to production. 

The right candidate will help ensure AI capabilities are reliable, measurable, supportable, cost-aware, and adopted effectively by the business. 

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