AI Project Manager

Seeking an AI Technical Project Manager to lead the adoption of AI-enabled products, platforms, and solutions across the organization. This role combines strong project management discipline with technical understanding of AI/ML technologies, data platforms, cloud infrastructure, and software engineering practices. The individual will coordinate cross-functional teams across Software Development, Infrastructure, Cybersecurity, Legal, Compliance, Risk Management and Vendor Management, manage delivery risks, align stakeholders, and ensure AI initiatives deliver measurable business value while meeting security, compliance, and governance requirements.

Main areas of responsibilities:

AI Program and Project Delivery

·      Lead end-to-end delivery of Generative AI, Agentic AI and Machine Learning initiatives.

·      Define project scope, objectives, success metrics, milestones, and delivery plans.

·      Establish and manage project schedules, budgets, resources, and dependencies.

·      Drive execution across multiple concurrent AI projects and workstreams including developer productivity and legacy code modernization platforms.

·      Monitor project progress and proactively address risks, blockers, and issues.

·      Build strong partnerships across Technology, Risk, Legal, Compliance, and Business teams.

·      Manage stakeholder expectations, priorities, and competing demands.

·      Act as the primary liaison between technology teams, control functions, legal and vendors.

·      Deliver clear and concise status updates to senior management and executive stakeholders

AI Governance, Risk & Compliance

·      Establish approved usage patterns, governance standards, and operating procedures.

·      Ensure AI projects comply with internal governance frameworks and regulatory requirements.

·      Coordinate risk assessments, legal reviews, cybersecurity evaluations, and compliance requirements.

·      Partner with Architecture and Engineering teams on integrations, security controls, and platform enhancements.

Technical Leadership & Coordination

·      Facilitate technical design discussions and challenge assumptions to optimize solutions.

·      Ensure alignment between AI solutions, enterprise architecture standards, cybersecurity requirements and infrastructure strategy.

·      Partner with AI Development, Cyber Security, Vendor Management and Infrastructure teams to ensure successful solution delivery.

Value Realization & Reporting

·      Define KPIs and success metrics for AI platforms.

·      Track utilization, productivity gains, cost optimization, and return on investment.

·      Build executive dashboards and adoption reporting.

·      Recommend expansion, optimization, or retirement of AI capabilities based on business value and usage data.

Qualifications:

Required

·      10+ years of Project Management, Program Management, or related experience.

·      3+ years leading Gen AI and Machine Learning initiatives.

·      Strong understanding of Generative AI, Agentic AI, AI SDLC, cloud platforms, developer productivity tools, and enterprise architecture concepts.

·      Experience working with cross-functional stakeholders including Engineering, Cyber, Risk, Compliance, and Legal.

·      Strong analytical, communication and executive presentation skills.

Preferred

·      Experience with GitHub Copilot, Azure Foundry, Claude Code or similar enterprise AI solutions.

·      Experience leading enterprise technology adoption and/or change management initiatives.

·      Familiarity with AI governance frameworks, software development practices, cloud platforms.

Preferred Certifications

·      Project Management Professional (PMP) or equivalent.

·      Generative AI Certification from Microsoft, AWS, Google, Databricks, or equivalent, covering LLMs, AI agents, retrieval-augmented generation (RAG), prompt engineering, enterprise AI architecture, security, and responsible AI.

Success Measures

·      Time-to-onboard new AI capabilities and use cases

·      Growth in active AI users and platform adoption

·      Productivity and efficiency gains achieved through AI

·      Successful implementation of cyber, legal, compliance and risk requirements

·      Demonstrated business value, cost savings, and ROI from AI investments