Technical delivery manager - ai & full-stack engineering

<p> About the Role: </p> <p> We are looking for a Technical Delivery Manager who combines strong delivery leadership with deep hands-on technical credibility. This is not a purely process-driven PM role — you'll be expected to go deep into Full Stack architecture discussions, review technical designs, understand AI/ML-based solutioning, and speak the language of engineers fluently, while owning end-to-end delivery accountability. </p> <p> Key Responsibilities: </p> Own end-to-end technical delivery for complex, multi-team engineering programs — scope, timelines, risk, quality, and stakeholder communication. Partner with engineering leads and architects to review solution designs, ensuring technical feasibility, scalability, and alignment with delivery timelines. Drive adoption of AI-based development practices within engineering teams — including Gen AI-assisted coding tools, LLM-based feature development, and AI-driven automation in the SDLC. Stay current on emerging AI trends and solutions (LLMs, Gen AI, agentic workflows, ML Ops) and evaluate their applicability to ongoing projects and client engagements. Act as a technical escalation point — capable of debugging delivery blockers that stem from actual code, architecture, or infrastructure issues, not just process gaps. Manage cross-functional teams (frontend, backend, Dev Ops, QA, data) across the full-stack development lifecycle. Define and track delivery metrics (velocity, quality, technical debt) and report to senior stakeholders/leadership. Facilitate Agile ceremonies (sprint planning, retros, stand-ups) while ensuring technical rigor isn't sacrificed for speed. Mentor engineering and delivery teams on best practices in both software delivery and AI-enabled development workflows. <p> Required Skills &amp; Experience: </p> Proven experience as a Technical Delivery Manager, Technical Program Manager, or similar hybrid delivery+engineering leadership role . Strong full-stack development background — hands-on or recent hands-on experience with modern stacks (e.g., Java/Spring Boot, Node.js, React/Angular, Python). Demonstrated experience integrating AI/ML or Gen AI solutions into products or internal engineering processes (e.g., LLM-powered features, AI coding copilots, intelligent automation). Solid understanding of cloud platforms (AWS/Azure/GCP), CI/CD pipelines, and microservices architecture. Experience managing delivery for complex, multi-stakeholder programs — ideally in a product or enterprise Saa S environment. Strong grasp of Agile/Scrum methodologies, with the judgment to know when to flex process for technical reality. Excellent stakeholder management and communication skills — able to translate technical nuance for non-technical leadership and vice versa. Experience of 10–15 years given the mix of deep technical + delivery leadership skills