Senior Staff Product Manager Technical (Data & Audience Platform Team), Hyderabad

About the Role

The Senior Staff Product Manager-Tech, AI/ML Roadmap and Platform Strategy, will define and drive the Data & Audience Platform (DAP) AI roadmap across predictive ML, GenAI, agentic workflows, AI-enabled analytics, data activation, and AI-native platform capabilities. This role is intentionally AI-centric: it exists to elevate DAP from a data and analytics platform organization into a product-led AI enablement function that identifies the highest-value AI opportunities, chooses the right technologies, and converts experimentation into durable business outcomes.

This role will be accountable for disciplined AI product strategy: selecting the right problems, validating that the newest technology is actually the best fit, defining measurable business value up front, and ensuring platform investments are reusable, governed, cost-aware, and scalable. The role will work across DAP, engineering, analytics, data science, architecture, product, operations, privacy/legal, AI governance, and senior leadership to make AI investments actionable, safe, and outcome driven.

Roles & Responsibilities:

- Shape AI product strategy and roadmap priorities across DAP platform areas.
- Evaluate AI/ML opportunities through value, feasibility, cost, data readiness, governance, and reuse lenses.
- Write AI-focused PRDs, product briefs, model/agent behavior requirements, evaluation criteria, and launch readiness requirements.
- Partner with engineering, data science, and architecture to compare model, platform, vendor, and implementation tradeoffs.
- Define KPIs and decision frameworks that connect AI outputs to business outcomes.
- Run AI roadmap,



prioritization, value review, and post-launch measurement forums.
- Translate complex AI/ML concepts into transparent executive narratives and actionable decisions.
- Identify when AI work should be standardized as a shared platform capability versus delivered as a bespoke solution.
- Work with cross-functional teams to intake, define, identify risks, and schedule work to develop key features.
- Formulate a point of view on how proposed features align with business goals and our tech strategy.

What to Bring:

- 12+ years of product management, technical product management, AI/ML product strategy, data platform, analytics, or related experience.
- Deep experience defining and delivering AI/ML, GenAI, data platform, customer intelligence, analytics, activation, or enterprise platform products at scale.
- Strong working knowledge of AI/ML product concepts including model lifecycle, experimentation, model evaluation, MLOps, data quality, governance, semantic layers, feature/data products, and post-launch performance measurement.
- Practical fluency in modern AI patterns such as LLMs, RAG, agentic systems, AI orchestration, prompt and agent lifecycle management, human-in-the-loop workflows, and AI observability.




- Demonstrated ability to set product vision and direction across multiple teams and highly ambiguous technical domains.
- Strong ability to evaluate technology tradeoffs across capability, quality, scalability, privacy, security, cost, maintainability, and business value.
- Excellent executive communication skills with the ability to translate technical AI concepts into clear decisions, narratives, and value cases.
- Proven ability to influence without authority across engineering, architecture, data science, TPM, analytics, operations, business, governance, and senior leadership teams.
- Track record of delivering measurable customer, business, operational, or platform impact from technical product investments.

The Nice to Haves

- Experience with streaming media, digital video, Customer 360, personalization, recommendations, content intelligence, advertising analytics, audience activation, commerce analytics, marketing analytics, or global platform products.
- Experience with AI governance, responsible AI, model risk review, privacy/security requirements, or compliance needs for AI-powered products.
- Experience creating scalable intake, prioritization, value management, and post-launch measurement mechanisms for AI portfolios.
- Experience with AI cost management, cloud/data platform FinOps, model inference cost tradeoffs, vendor evaluation, or build/buy/reuse decisioning.
- Experience mentoring senior PMs / PM-Ts and raising product craft across a matrixed organization.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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