Program Manager (Tech + AI driven Program Management) - Naukri.com
Info Edge
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Job summary
Info Edge is seeking a Program Manager to lead AI-powered program governance, delivery, and stakeholder management. The role emphasizes strong product engineering exposure, Sarbanes-like governance, and hands-on use of AI tools to enhance reporting and decision-making.
The ideal candidate brings 8-12 years in IT, 5+ years in program management, and a proven ability to drive initiatives across cross-functional teams in a matrix organization.
Qualifications
- Engineering degree and MBA from a top-tier institute.
- 8-12 years IT experience with at least 5 years in project/program management.
- Advanced communication and facilitation; formal training preferred.
- Advanced presentation skills; comfortable with senior audiences.
- Experience with PM tools (Jira, Confluence, Azure DevOps) and data dashboards.
Responsibilities
- Assess cross-functional impacts and drive alignment across Engineering, Product, Design, Sales and Business teams.
- Own end-to-end accountability for delivering measurable business outcomes.
- Lead portfolio governance, planning and delivery as Chief Scrum Master for the program.
- Publish timely status reports, dashboards, risks and dependencies to leadership.
- Drive AI-driven automation and analytics to improve governance and decision-making.
Skills
Education
Tools
Job description
Tech + AI Driven Program Management
The ideal candidate should have an Engineering degree with an MBA from a top-tier institute, possessing 810
years of IT experience, including at least 5 years in Project/Program Management. The candidate should have
strong product engineering exposure, exceptional stakeholder management skills, and hands‑on experience
leveraging AI-powered tools and automation to improve program governance, execution, and decision‑making.
- Engineering + MBA from Top tier institute.
- 8-12 years experience including minimum 5 years expertise in project or program management domain.
- Advanced communication and facilitation skills. Formal training preferred.
- Advanced presentation skills. Demonstrated comfort in presenting to senior level cross functional audiences.
- Demonstrated working knowledge of advanced concepts with program management approaches, tools and
methodologies. PMP/CSM certification preferred.
- Extensive experience in full life cycle of project management, including planning, budgeting, estimating.
- Proven expertise as Chief Scrum Master for team, support in managing & executing sprint ceremonies.
- Good knowledge of Engineering concepts and agile or project management tools viz. JIRA, Confluence,
Power BI, etc.
- Strong analytical, problem solving and decision‑making skills.
- Strong aptitude and attitude for working in a Matrix organization in IC role.
- Well versed with Agile methodologies i.e. SCRUM & KANBAN.
- Product Management collaboration with Risk & Dependency Management
- Executive Stakeholder Management with Data Analysis & Dashboarding (Excel, Power BI/Tableau)
- Jira, Confluence, Azure DevOps with Engineering & SDLC Understanding
- Workflow Automation (Power Automate, Zapier, Make, or similar)
- Hands‑on experience leveraging AI tools and capabilities (ChatGPT, Microsoft Copilot, Gemini, Claude, NotebookLM, etc.) for program and project management including automated status reporting, meeting summarization, risk prediction, dashboarding, and workflow automation.
- Demonstrate the ability to assess cross-functional impacts of decisions and proactively drive alignment
across Engineering, Product, Design, Sales, and Business teams.
- Understand the business objectives of programs and assume end-to-end accountability for delivering measurable business outcomes.
- Own successful delivery of strategic programs through effective planning, execution, governance, and stakeholder management.
- Review and govern the overall portfolio, ensuring projects are prioritized, planned, and executed in alignment with business goals.
- Act as Chief Scrum Master for the portfolio and facilitate sprint planning, stand-ups, retrospectives, backlog grooming, and release planning.
- Drive regular interactions with Product, Engineering, QA, Design, Analytics, Sales, and Leadership teams to ensure seamless execution.
- Demonstrate excellent process thinking by documenting workflows, identifying bottlenecks, and driving process standardization.
- Publish timely status reports, dashboards, executive summaries, risks, dependencies, metrics, and portfolio health updates.
- Generate regular and ad‑hoc insights from multiple data sources, ensuring data accuracy while identifying leading indicators and business risks.
- Manage stakeholder expectations and proactively resolve critical escalations.
- Build strong collaborative relationships across cross‑functional teams to ensure effective program execution.
- Identify, quantify, mitigate, and track risks, issues, dependencies, and change requests throughout the program lifecycle.
- Assess business impact of risks and drive mitigation plans with clear ownership.
- Drive executive communication through concise, data‑driven updates and leadership reviews.
- Demonstrate strong organizational skills with the ability to manage multiple concurrent strategic initiatives.
- Drive continuous improvement initiatives by identifying opportunities for operational excellence and automation.
- Roll up sleeves to actively participate in execution discussions and remove delivery bottlenecks.
- Understand engineering architecture, software development lifecycle, and facilitate technical discussions across teams to drive closure.
- Leverage Generative AI and AI-powered productivity tools (ChatGPT, Microsoft Copilot, Gemini, Claude,
etc.) to improve program execution, governance, reporting, and stakeholder communication.
- Design and implement AI-assisted program governance frameworks, including automated status reporting,
meeting summaries, action-item tracking, risk identification, and executive dashboards.
- Build AI-powered workflows for project tracking, requirement summarization, sprint analysis, dependency
management, and portfolio health monitoring.
- Use AI to analyze program metrics, identify trends, predict delivery risks, recommend corrective actions,
and improve decision‑making.
- Drive adoption of AI across Product and Engineering teams to improve productivity, documentation quality,
and operational efficiency.
- Collaborate with Data, Engineering, and Product teams to identify AI‑led automation opportunities across
SDLC and business processes.
- Evaluate emerging AI tools and recommend solutions that improve delivery efficiency, resource utilization,
and stakeholder experience.
- Develop prompts, AI copilots, and reusable templates to automate repetitive Program Management
activities.
- Champion an AI-first mindset by continuously improving processes through intelligent automation while
ensuring responsible and secure AI adoption.
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