Product Owner (AI)

Role Summary

InvoiceCloud is hiring aProduct Owner AIto drive day-to-day execution for our newly formedAI Development Teamin Hyderabad. Reporting to theVP of Product Strategy you will partner closely with theLead Product ManagerEngineering Team Lead andPrincipal Engineerto ship AI-enabled modules from concept to productionquickly safely and with strong measurement.

This role is anindividual contributorproduct role with a clear emphasis ondelivery excellence: keeping work continuously groomed and ready driving crisp requirements coordinating dependencies and ensuring each release meets quality bars for evaluation telemetry and observability.

WhatYoullDo

• Own execution for the AI team backlog:translate product intent into well-scoped epics/stories clear acceptance criteria and predictable sprint plans that keep the team unblocked and moving.

• Maintain 3 sprints ready hygiene:ensure the team has 3 sprints of groomed prioritized work with dependenciesidentifiedearly and resolved through proactive coordination.

• Ship incrementally not in big bangs:structure delivery into thin testable slices (pilots expanded cohorts GA) with explicit release criteria and rollback plans where needed.

• Build production-grade AI feature readiness:partner with engineering and the principal AIleadto ensure every AI capability includes:

• evaluation strategy (offline online whereappropriate)

• quality and safety checks

• telemetry/observability

• and clear thresholds for launch decisions.

• Run a clean operating cadence:lead sprint-level rituals and product execution rhythms (grooming pre-planning risk/dependency reviews) so stakeholders have visibility and there are fewer surprises.

• Drive cross-functional alignment:coordinate with stakeholdersto launch AI modules responsibly (e.g. Security/Compliance Customer Success Support Implementations) as those motions are defined.

• Turn ambiguity into decisions:document key decisions tradeoffs and open questions; drive closure with options and recommendations.

• Measure what matters:define andmaintainmodule-level scorecards (adoption performance quality latency deflection/efficiency outcomes as applicable) and communicate progress with high signal and low noise.

What Success Looks Like (First 30/60/90 Days)

First30 days

• Youvealigned with the VP of Product Strategy Lead PM Engineering Lead and Principal Engineer on near-term scope.

• A single sourceof truth is live (Jira/Confluence) with clear definitions of ready done decision logs and an execution cadence.

• Backlog hygiene isestablishedand the team is consistently grooming toward a3-sprints-readyposture.

By60 days

• The AI team hasthree sprints fully groomedwith clear acceptance criteria dependencies and sequencing.

• At least one module has a defined evaluation plan and instrumentation/observability implemented end-to-end (not bolted on late).

• Delivery istracking toexpectations via incremental testable releases (pilot-ready slices rather than large multi-sprint all-or-nothing scopes).

By90 days

• AI offeringsdemonstratebest-in-class evaluation discipline(repeatable evaluationsmonitoredmetrics and release gating based on quality thresholds).

• Telemetry and observability support ongoing improvement and incident response (quality drift detection usage insights and clear ownership for follow-up actions).

• Stakeholders describe delivery aspredictable and incremental with fewer late surprises and clearer decision-making.

What You Bring (Required)

• Product management experience in B2B SaaS (often 4 years but we value depth of ownership and outcomes over a strict number).

• Hands-on experience with LLM/RAG/agentic systemsincluding translating them into real user workflows and shipping to production.

• Delivered agents to production with robust evaluation frameworks:you can describe how youmeasuredquality (and failure modes) validated changes andmonitoredperformance over time.

• Strong execution instincts: you can run sprint-level planning keep a backlog ready manage dependencies and drive teams toward incremental delivery.

• Technical fluency to collaborate credibly with engineering and AI stakeholders (APIs data flows instrumentation/telemetry andproductionreadiness concepts).

• Excellent written communication: crisp requirements decision documentation and stakeholder updates that reduce ambiguity and rework.

Nice to Have

• Payments / EBPP / fintech domain experience.

• Experience partnering on AI governance (data handling human-in-the-loop decisions auditability) for customer-facing AI.

• Familiarity with product/data tooling such asJira/Confluence Pendo Snowflake Tableau.

• Experience with modern AI product patterns (e.g. function calling tool use orchestration patterns) and/or experimentation practices for AI systems.

HowYoullUse AI in This Role

We expect you to use AI as a practical force multiplier to improve how youoperatewhile applying sound judgment validation and data-handling discipline.

In this roleyoulluse AI to:

• Accelerate requirements and backlog quality:convert discovery notes and technical discussions into clearer epics user stories acceptance criteria and test casesthenvalidatewith engineering.

• Improve delivery predictability:summarize Jira/Confluence signals to spot emerging risks dependency collisions or scope creep early (before they become late escalations).

• Strengthen evaluation discipline:help structure evaluation plans track experiments compare model/prompt/tooling changes and turn results into release decisions stakeholders can trust.

• Turn meetings into action:transform notes into owners next steps due dates and decision logs to reduce lost decisions and ensure follow-through.

• Automate lightweight reporting:draft weekly status updates and dashboards that reflect real progress and risksvalidatedagainst source systems before sharing.

Why Join / What We Offer

Youllbe part of a new dedicated AI team with the mandate to deliver real customer valuequicklybuildingthe operating model for how InvoiceCloud ships AI responsibly and at scale.

Location / Travel

• Location model:Hyderabad (office-based)

• Travel:Minimal; not expected