About the Role:
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.
Key Responsibilities:
- 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 GenAI-assisted coding tools, LLM-based feature development, and AI-driven automation in the SDLC.
- Stay current on emerging AI trends and solutions (LLMs, GenAI, 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, DevOps, 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.
Required Skills & Experience:
- 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 GenAI 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 SaaS 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
