Technical Product Owner – AI/ML, Cloud & Data Platforms (Immediate Joiners Preferred)

Technical Product Owner AI/ML, Cloud, or Data Platforms

Experience: 1015 Years

Location: Bengaluru / Chennai / Noida / Pune / Hyderabad

Role Overview

We are seeking a highly skilled Technical Product Owner (TPO) who blends strong business product leadership with deep technical understanding across AI/ML, data engineering, and cloud platforms.

In this role, you will own the vision, roadmap, and measurable business outcomes for AI-powered, cloud-native, and data-driven platform capabilities. You will translate strategic objectives into technical deliverables, manage the product backlog, guide engineering execution, and ensure delivery of scalable, enterprise-grade solutions.

This position requires a leader who can bridge business strategy, technology architecture, and engineering execution, ensuring that every initiative drives tangible business value while adhering to enterprise standards and Responsible AI principles.

Key Responsibilities

A. Strategic Product Ownership (Business-Focused Responsibilities)

• Define and articulate the product vision, strategy, roadmap, and success metrics for AI/ML, cloud, or data platform initiatives.
• Align product strategy to organizational OKRs, ROI goals, digital transformation priorities, and AI adoption strategy.
• Partner with business stakeholders to translate high-level use cases (e.g., personalization, forecasting, NLP, anomaly detection) into actionable requirements.
• Establish value hypotheses, track business KPIs, and demonstrate impact on efficiency, automation, revenue enablement, and customer experience.
• Prioritize product investments based on value, risk, complexity, and organizational readiness.
• Champion Responsible AI, data ethics, compliance, and governance practices.

B. Technical / Tactical Product Ownership (Execution Responsibilities)

• Own and continuously refine the product backlogincluding epics, user stories, data pipelines, ML lifecycle features, and platform capabilities.
• Collaborate with data engineering, ML engineering, cloud architecture, security, and MLOps teams to design scalable end-to-end solutions.
• Define technical acceptance criteria for models, APIs, data flows, pipelines, and inference systems.
• Ensure alignment between data availability, model readiness, infrastructure requirements, and deployment environments.
• Work with MLOps teams to establish standardized processes for deployment, monitoring, drift detection, and retraining.
• Contribute to architectural decisions, reusable component development, platform modernization, and cloud-native design patterns.
• Drive Agile ceremoniessprint planning, backlog grooming, and release management.
• Track and report technical KPIs including model performance, latency, data quality SLAs, deployment frequency, and system reliability.