Job Summary
This role operationalises the definition and delivery of AI driven product features by translating product insights into actionable requirements and prioritised roadmaps. The role partners closely with engineering, architecture, practice leaders, and ecosystem partners to deliver scalable, reliable, and responsible AI capabilities. This position requires strong techno functional acumen, data driven execution, and ownership of outcomes across delivery, adoption, and business impact.
Key Responsibilities
- Translate business and product insights into clear product requirements, user stories, and prioritized backlogs for AI‑driven features and automation frameworks.
- Collaborate with engineering teams and architects to define technical feasibility, scope boundaries, iteration plans, and delivery milestones for AI capabilities.
- Define and track success metrics, acceptance criteria, and telemetry signals covering performance, quality, safety, and adoption outcomes.
- Coordinate cross‑functional execution across engineering, GTM, alliances, and practice teams to maintain delivery cadence and stakeholder alignment.
- Support Responsible AI readiness by embedding risk considerations, documentation needs, evaluation checkpoints, and guardrails into product planning and execution.
- Leverage hyperscaler ecosystems (Azure, AWS, Google Cloud) and partner toolchains to enable scalable, explainable, and enterprise‑ready AI solutions.
- Monitor post‑launch performance and adoption metrics, using data insights to continuously improve product value, reliability, and customer impact.
Skill Requirements
• BE / BTech / MBA or equivalent, with a strong foundation in technology led product delivery or AI driven solution development.
• 6+ years of experience in product management, solution ownership, or techno functional roles within IT services, platforms, or AI led products.
• Hands on experience working with generative AI, ML enabled solutions, or intelligent automation use cases across enterprise environments.
• Exposure to hyperscaler platforms (Azure, AWS, Google Cloud) and familiarity with AI service stacks, tooling, and partner ecosystems.
• Demonstrated ability to work across engineering, architecture, and business stakeholders to drive execution and measurable outcomes