Technical Project Manager

Job description The Technical Project Manager will oversee the end‑to‑end delivery of enterprise digital and AI platform initiatives, including the implementation of foundational capabilities for AI/LLM/Multi‑Agent platforms across business units. The role is accountable for planning, coordination, execution, and delivery of complex platform components such as Model & Inference Gateway, Shared Agent Runtime, Shared RAG Service, Developer Portal, ML Training Plane. This role requires a hands‑on, technically fluent project manager who can independently reason through technical issues, engage deeply with architects on design decisions, and effectively represent the engineering perspective in stakeholder discussions. Key Responsibilities Project Delivery Deliver complex AI projects end‑to‑end, from initiation through production rollout. Develop and maintain detailed project plans, schedules, milestones, and delivery roadmaps. Track progress across multiple technical workstreams (design, platform services, integrations, security, operations, vendors). Manage scope, dependencies, risks, and issues to ensure timely delivery of MVPs and phased releases. Coordination & Execution Work closely with engineering teams, solution architects, security, and business stakeholders to clarify requirements and align deliverables. Act as a single point of coordination across internal teams, external vendors, and technology partners. - Facilitate sprint ceremonies, technical working sessions, and cross‑functional alignment forums. Technical Engagement Independently troubleshoot technical concerns at a fundamental (101) level using first principles reasoning, without relying on engineering teams for basic analysis. Translate technical challenges into clear options, risks, and next steps to move discussions forward. Actively engage with solution architects on architectural and design decisions, asking informed questions and validating alignment with business and delivery constraints. Understand core platform components well enough to break down technical requirements into executable project tasks. Governance & Reporting Maintain accurate status reports, RAID logs, dashboards, and delivery metrics. Communicate progress, risks, blockers, and mitigation plans clearly and confidently to leadership and stakeholders. Ensure compliance with security, governance, AI Safety, and Responsible AI standards throughout the delivery lifecycle. Adoption & Stakeholder Management Support onboarding of pilot use cases onto shared platforms. Coordinate documentation, training materials, and developer enablement activities to drive adoption. Serve as a trusted interface between technical teams and non‑technical stakeholders. Qualifications Education: Bachelor’s in Computer Science, Engineering, IT, or related field. Experience: 5–8 years of experience as a Project Manager or Technical Project Manager delivering enterprise digital or platform projects. Demonstrated delivery of at least two digital projects end‑to‑end. Experience managing multi‑team, technically complex programs with dependencies across engineering, architecture, and vendors. Working as a developer/team lead that completed end-to-end bespoke projects. Exposure to cloud platforms, AI/ML systems (including technologies such as RAG and MCP), or large‑scale enterprise technology programs preferred. Skills: Strong technical foundation enabling independent troubleshooting and reasoning at a conceptual level. Ability to engage in meaningful architectural conversations with solution architects. Excellent communication skills — able to articulate technical concepts clearly to both technical and non‑technical audiences. Strong stakeholder management, risk mitigation, and issue resolution capabilities. - Proficiency in Agile, Scrum, or hybrid delivery models. Success Metrics Successful end‑to‑end delivery of defined digital and AI platform initiatives. Effective technical decision support and issue resolution without over‑escalation. Clear, proactive communication with stakeholders and leadership. Minimal delivery risks and smooth cross‑team execution. High satisfaction from engineering teams and business partners.