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Technical Product Manager - AI Products

Job in 411001, Pune, Maharashtra, India
Listing for: omniXM
Full Time position
Listed on 2026-06-17
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Product Designer, Product Engineer
Job Description & How to Apply Below
Location:

Pune - On-Site
Type:
Full-Time
Reporting To:
Head of Engineering

ABOUT omniXM
omniXM is a fast-growing SaaS company building intelligent customer experience management products. Our flagship AI product, omniXMOS, includes a conversational survey analysis engine, omni Sense, that processes real-world business feedback  system combines deterministic data tools, LLM-powered reasoning, multi-modal report generation, and document-grounded RAG - all served through a FastAPI backend and deployed on Azure.
We are scaling our Product team to drive the next phase of omni Sense: smarter agentic workflows, richer insights, and AI experiences our customers can trust. We are looking for an experienced Technical Product Manager to own product development end-to-end and partner closely with our AI Engineering team.

THE ROLE
As our Technical Product Manager, you will own all aspects of the product life cycle - the technical, functional, and business foundations of our AI products. You will act as the liaison between cross-functional teams including AI Engineering, Design, QA, Change Management, Customer Success, and Sales. Your goal is to translate ambiguous business problems and emerging AI capabilities into clear, well-scoped, shippable products.
This is a senior, hands-on role. You will gather requirements, create wireframes and workflows, describe them clearly to the development team, work with QA to validate delivery, and personally validate that what ships matches the requirements. You will be the Product Owner for an AI engineering team building probabilistic, LLM-powered systems - which means you must be comfortable defining requirements and acceptance criteria for features that do not behave deterministically.
Please do not apply if you do not have 8+ years of experience creating BRDs / PRDs / FRDs, building wireframes and user flows, running scrum ceremonies, and leading the SDLC for software products.

ROLES & RESPONSIBILITIES
1. Product Vision & Roadmap

· Define and maintain the product roadmap for omni Sense and adjacent AI capabilities, in alignment with business objectives and customer needs.

· Translate market signals, customer feedback, and AI engineering possibilities into a prioritized, outcome-driven roadmap.

· Make explicit build / buy / defer decisions and clearly communicate the rationale and trade-offs behind them.

2. Requirements & Specification

· Gather and elicit requirements from stakeholders, then create and maintain comprehensive BRDs / PRDs / FRDs detailing functional and non-functional requirements.

· Write clear acceptance criteria and definitions of done - including for AI/LLM features where outputs are probabilistic (quality bars, confidence thresholds, guardrails, and acceptable failure modes).

· Develop detailed wireframes, prototypes, and workflow / user-flow diagrams to communicate design and interaction concepts, including how users review, trust, and act on AI-generated output.

3. Sprint Planning, Delivery & Product Ownership

· Act as the Product Owner for the AI Engineering team: own and prioritize the backlog and ensure alignment with the product vision.

· Describe requirements, wireframes, and workflows to the development team via developer-ready stories and clear handoffs, removing ambiguity before and during a sprint.

· Lead and facilitate SCRUM ceremonies - sprint planning, daily stand-ups, reviews, and retrospectives - and own the sprint goal and the team's commitment.

· Drive sprint execution: track progress, remove blockers, and manage scope during the sprint to keep delivery on track.

· Monitor and improve team velocity, throughput, and predictability (burndown, capacity planning) to forecast delivery and continuously improve the team's cadence.

· Manage the product release process end-to-end, coordinating across engineering, design, QA, and business teams.

4. Validation & Quality

· Write thorough test cases and partner with QA to validate that delivered functionality meets the requirements - including evaluation of probabilistic AI output quality.

· Personally validate and sign off that what is built matches the intent and acceptance criteria of the requirements.

·…
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