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Hexaware Technologies

Application Project Manager

Posted 4 Days Ago
Remote
Hiring Remotely in India
Expert/Leader
Remote
Hiring Remotely in India
Expert/Leader
Lead multifaceted technology projects including application development and engineering, ensuring adherence to SDLC and Agile practices, while driving metrics-driven execution.
The summary above was generated by AI
Grade: G7 TSR : Application Project Manager Overview We are seeking a seasoned Project Manager (10+ years experience) with a strong track record of successfully delivering diverse technology projects including application development, testing, migration, data, and engineering initiatives. The ideal candidate brings deep SDLC expertise, excels in project planning and metrics-driven execution, and is highly proficient in Agile/Scrum methodologies. This role requires a leader who can step into a Scrum Master role when needed, dive deep into execution details when projects go off track, and drive a shift-left approach with an AI-first mindset to improve quality, predictability, and outcomes. Key Responsibilities Lead end-to-end delivery of multiple project types including development, testing, migration, data, and engineering programs. Own project planning, estimation, scheduling, risk management, and dependency management across the project lifecycle. Ensure strong adherence to SDLC fundamentals, governance standards, and delivery best practices. Drive Agile/Scrum execution, including sprint planning, daily stand-ups, reviews, retrospectives, and backlog refinement. Act as Scrum Master when required, ensuring Agile principles are effectively followed and impediments are removed. Track, analyze, and report key delivery metrics (schedule, cost, quality, velocity, productivity, risk, and customer satisfaction). Proactively identify delivery risks and deep-dive into technical and functional details to course-correct projects that are off track. Enable a shift-left mindset by promoting early validation, test-first approaches, automation, and proactive risk identification. Apply an AI-driven mindset to improve planning accuracy, forecasting, quality assurance, productivity, and decision-making. Collaborate closely with engineering, QA, data, architecture, and business stakeholders to ensure alignment and transparency.

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