Please have a look at the updated JD.
Job Title: Technical Project Manager
Experience: 10+ years (minimum 3 years running multi-team programmes)
Location / Work Mode: Hyderabad/Hybrid
Employment Type: Full-time
About the Role
We are hiring a Technical Project Manager to lead a time-bound AI workforce transformation programme. The programme introduces AI tools and new ways of working across teams in the software development lifecycle, using a phased, evidence-gated approach: mobilize, discovery, baseline, solution design, implementation and measurement.
This is a governance-heavy, metrics-driven delivery role. You will turn the methodology into a dated, committed programme plan, hold owners accountable to it, and give leadership one reliable view of progress, risks and decisions needed. You will work closely with architecture and engineering teams, team leads, tool admins, security/compliance and finance.
Key Responsibilities
Project Planning and Schedule
- Build and own the project schedule, with phase-wise, per-team and per-intervention milestones.
- Deliver the indicative project timeline within the first 30 days and keep it current.
- Flag variances early and escalate with options, with no silent slippage.
Governance and Cadence
- Run the weekly written status to sponsors, steering committee sessions and phase-exit playbacks with team leads.
- Enforce exit gates: no phase closes without signed-off deliverables, and no intervention starts without a frozen, evidence-backed baseline.
- Bring scale / iterate / retire decisions to steering on schedule for every intervention.
Dependencies, Risks and Pipeline
- Track and clear cross-team dependencies and blockers across team leads, tool admins, security/compliance and finance.
- Maintain the risk and dependency register with a weekly refresh.
- Manage the intervention pipeline: prioritized backlog, pilot schedules and rollout waves.
Adoption and Programme Record
- Coordinate enablement during pilots and rollouts, including training sessions, champions and office hours.
- Maintain the single source of truth: versioned template repository, baseline snapshots and decision log.
- Report programme economics with the AI & Architecture team: tool spend, licence utilisation and measured return per intervention.
Must-Have Skills
- 10+ years managing software delivery programmes, including multi-team initiatives with formal governance, gates and steering committees.
- Working knowledge of DORA and flow metrics (lead time, cycle time, deployment frequency, MTTR) and baseline vs target tracking.
- Experience running change and adoption programmes: training plans, champions networks and usage tracking.
- Strong stakeholder management with client leadership and delivery teams, and crisp written reporting.
- Fluency in Jira / Azure DevOps, Git platforms and CI/CD, enough to interrogate delivery data.
- Risk, dependency and escalation management.
Good to Have
- Exposure to AI coding assistants, test generation and CI/CD analytics.
- Experience with offshore or captive-centre delivery models.
- Scrum / SAFe / LeSS or multi-squad agile coordination.
- Tools: [MS Project / Smartsheet, Confluence, Power BI / Tableau].
Qualifications
- Bachelor's degree in Engineering, Computer Science or a related field (or equivalent). MBA is a plus.
- Preferred certifications: PMP / PRINCE2, PMI-ACP, SAFe Program Consultant or equivalent.
- Track record of time-bound delivery under formal governance, verifiable through references.
What We Look For
- Evidence-first: you rely on data over anecdote and are comfortable telling leadership what the numbers say.
- Firm on process, collaborative in style: you enforce gates without alienating delivery teams.
- Calm and structured: you prioritise well across concurrent workstreams.
- Strong written communication: weekly status and steering packs are core deliverables.
- Change-sensitive: you make teams experience the programme as enablement, not surveillance.
What We Offer
- Ownership of a high-visibility, leadership-sponsored transformation programme from the start.
- Direct exposure to AI-in-SDLC adoption at enterprise scale.
- Work alongside a dedicated AI and architecture practice with a defined methodology.
- Compensation of [₹ range] with a structured performance review process.
- Support for certifications, conferences and emerging tooling.
