AI Product Owner

TING; Ernakulam; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

TING is seeking an AI product owner to bridge stakeholders and the builders. You will own discovery, requirements and delivery rhythm for AI features across internal AI layer, internal platform and client engagements, with product leadership guiding direction and you executing.

You'll write clear product requirements, define acceptance criteria around model behavior, manage the AI feature backlog, run sprint ceremonies, and measure adoption and impact to ensure real value is delivered.

Qualifications

• 3+ years in product ownership, business analysis, or similar delivery role.
• Strong written communication; documents must be unambiguous.
• Working understanding of LLM product behavior and failure modes.
• Ability to work with senior stakeholders and explain feasibility.
• Comfort with ambiguity in requirements.

Responsibilities

• Run discovery with internal teams across operations, finance, HR, creative and PMO to find where AI genuinely removes work.
• Write product requirement documents that engineers can build from without a follow up meeting, including acceptance criteria that account for model behaviour.
• Own and prioritise the backlog for AI features across both internal platforms, and run sprint ceremonies for the pod.
• Define and track adoption and impact metrics. If a feature ships and nobody uses it, that is yours to surface and fix.
• Support client engagements with requirement gathering, scope documentation and stakeholder communication.
• Coordinate user acceptance testing, rollout, internal enablement and documentation.

Skills

Product ownership

Business analysis

Written communication

AI/LLM understanding

Tools

SQL

Job description

This role sits between the people who need something and the people who build it. You will own discovery, requirements and delivery rhythm for AI features across our internal AI intelligence layer, our internal operating platform and client engagements, with product leadership setting direction and you running the execution.

AI product work differs from standard product work in one important way: the output is probabilistic. A feature is not simply built or not built, it is built to a quality level that has to be defined, measured and defended. A good part of this job is making that definition concrete enough for an engineer to build against and an executive to sign off on.

WHAT YOU WILL DO

• Run discovery with internal teams across operations, finance, HR, creative and PMO to find where AI genuinely removes work rather than adding a layer over it.
• Write product requirement documents that engineers can build from without a follow up meeting, including acceptance criteria that account for model behaviour rather than assuming deterministic output.
• Own and prioritise the backlog for AI features across both internal platforms, and run sprint ceremonies for the pod.
• Define and track adoption and impact metrics. If a feature ships and nobody uses it, that is yours to surface and fix.
• Support client engagements with requirement gathering, scope documentation and stakeholder communication.
• Coordinate user acceptance testing, rollout, internal enablement and documentation.

WHAT WE ARE LOOKING FOR

• Three or more years in product ownership, business analysis or a comparable delivery role, with at least one year on technically substantial products.
• Genuinely strong written communication. A large share of this job is documents, and they need to be unambiguous.
• A working understanding of how LLM products behave, including why they fail and what that means for scoping. You do not need to build them, but you cannot treat them as a black box that either works or does not.
• Confidence with stakeholders more senior than you, including the ability to say a request is not feasible and explain why.
• Comfort with ambiguity. Requirements here often begin as a vague complaint about a process.

USEFUL BUT NOT ESSENTIAL

• Agile or Scrum certification, particularly CSPO.
• Experience with internal platform or enterprise tooling products, where adoption is the hardest problem.
• Exposure to AI governance, data privacy or access control requirements.
• Basic SQL, enough to answer your own questions about usage data.

WHAT SUCCESS LOOKS LIKE

In your first ninety days you will own the delivery cycle for one product area end to end, and establish an adoption measurement baseline that did not exist before you arrived.