Job Title: Technical Product Owner – AI/ML or Cloud or Data Platforms
Experience: 10-15 Years
Location: [Bengaluru / Pune / Gurgaon]
Employment Type: Full-time
Role Overview
We are seeking a Technical Product Owner (TPO) who combines strategic business ownership with strong technical understanding of AI/ML or data or cloud ecosystems
You will define the vision, roadmap and measurable outcomes for data-driven/ Cloud and AI-powered products while also owning the backlog, technical decisions and delivery of platform capabilities.
This role demands an ability to bridge business strategy and engineering execution ensuring every technical initiative drives tangible business impact and adheres to enterprise standards.
Key Responsibilities
- Business Product Ownership (Strategic PO Responsibilities)
- Define and communicate the product vision, roadmap and business outcomes for AI/ML/ Cloud or data platform initiatives.
- Align the AI/ML product strategy with organizational OKRs, ROI goals and digital transformation objectives.
- Partner with business leaders to translate high-level use cases (e.g., personalization, forecasting, anomaly detection) into actionable technical features.
- Define value hypotheses, track business KPIs and report impact on efficiency, automation and customer experience.
- Prioritize investments based on business value risk and readiness.
- Champion Responsible AI and ethical data use as part of business governance.
- Tactical / Technical Product Ownership (Execution-Level Responsibilities)
- Own the backlog including epics, user stories, data pipelines, model lifecycle features and infrastructure capabilities.
- Collaborate with data engineers, ML engineers and cloud architects to design scalable solutions for data ingestion, training and inference.
- Define technical acceptance criteria for ML features, APIs and pipelines.
- Ensure strong alignment between data availability, model readiness and deployment environments.
- Partner with the MLOps team to standardize model deployment, monitoring and retraining processes.
- Contribute to architecture discussions, data platform evolution and reusable component development.
- Manage sprint ceremonies, backlog grooming and release planning with engineering teams.
- Track progress via technical KPIs (e.g., model latency, data quality SLAs, deployment frequency).
Technical Environment / Stack Awareness
Domain
Key Tools / Platforms
Cloud Platforms
Azure (ADF, Synapse, ML Studio), AWS (Glue, Redshift, SageMaker), GCP (BigQuery, Vertex AI)
Data Engineering
Databricks, Apache Spark, Airflow, Kafka, Delta Lake, Snowflake
MLOps & Deployment
MLflow, Kubeflow, Docker, Kubernetes, DVC, GitHub Actions
AI/ML Frameworks
Scikit-learn, PyTorch, TensorFlow, Hugging Face (conceptual)
GenAI & LLM Ecosystem
LangChain, OpenAI API, Vertex AI, Azure OpenAI, Pinecone, FAISS
Analytics & BI
Power BI, Tableau, Looker
Governance & Monitoring
Data Catalog, Lineage, SHAP, LIME, Model Monitoring
Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science or Engineering.
- 10+ years of experience in product ownership, technical program management or AI/ML delivery.
- Strong knowledge of AI/ML model lifecycle, data pipelines and cloud-native architecture.
- Proven ability to balance business priorities with technical feasibility.
- Experience in Agile / Scrum environments writing epics, managing sprints and working with cross-functional teams.
- Exposure to LLM/GenAI, data modernization or AI platform products preferred.
Certifications (Preferred)
- Certified Scrum Product Owner (CSPO) or Professional Scrum Product Owner (PSPO).
- Microsoft / AWS / GCP certifications in AI, Data or Cloud.
- Any recognized AI Product Management or Responsible AI certification.
Soft Skills
- Strong communication and stakeholder management able to engage with business, engineering and data science leaders.
- Analytical mindset; capable of linking technical metrics to business KPIs.
- Skilled in prioritization, trade-off decisions and dependency management.
- Growth mindset and adaptability to emerging AI technologies.
Product Management, Gen AI, Azure
