Product Owner (AI) Full Time

InvoiceCloud is a fast-growing fintech leader recognized with 20 major awards in 2025, including USA TODAY and Boston Globe Top Workplaces, multiple SaaS Awards wins for Best Solution for Finance and FinTech, and national customer service honors from Stevie and the Business Intelligence Group. Judges also highlighted our mission to reduce digital exclusion and restore simplicity and dignity to how people pay for essential services, as well as our leadership in AI maturity and responsible innovation. It’s an award-winning, purpose-driven environment where top talent thrives. To learn more, visit InvoiceCloud.com.

Role Summary

InvoiceCloud is hiring a Product Owner, AI to drive day-to-day execution for our newly formed AI Development Team in Hyderabad. Reporting to the VP of Product Strategy, you will partner closely with the Lead Product Manager, Engineering Team Lead, and Principal Engineer to ship AI-enabled modules from concept to production—quickly, safely, and with strong measurement.

This role is an individual contributor product role with a clear emphasis on delivery excellence: keeping work continuously groomed and ready, driving crisp requirements, coordinating dependencies, and ensuring each release meets quality bars for evaluation, telemetry, and observability.

What You’ll Do

• 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 dependencies identified early 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 AI lead to ensure every AI capability includes:
• evaluation strategy (offline + online where appropriate),
• 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 stakeholders required to 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 and maintain module-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)

First 30 days

• You’ve aligned with the VP of Product Strategy, Lead PM, Engineering Lead, and Principal Engineer on near-term scope.
• A single source of truth is live (Jira/Confluence) with clear definitions of “ready,” “done,” decision logs, and an execution cadence.
• Backlog hygiene is established and the team is consistently grooming toward a 3-sprints-ready posture.

By 60 days

• The AI team has three sprints fully groomed with 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 is tracking to expectations via incremental, testable releases (pilot-ready slices rather than large multi-sprint “all-or-nothing” scopes).

By 90 days

• AI offerings demonstrate best-in-class evaluation discipline (repeatable evaluations, monitored metrics, 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 as predictable and incremental, with fewer late surprises and clearer decision-making.

What You Bring (Required)

• Product management experience in B2B SaaS (4+ years, but we value depth of ownership and outcomes over a strict number).
• Hands-on experience with LLM/RAG/agentic systems—including translating them into real user workflows and shipping to production.
• Delivered agents to production with robust evaluation frameworks: you can describe how you measured quality (and failure modes), validated changes, and monitored performance 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, and production readiness 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 as Jira/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.

How You’ll Use AI in This Role

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

In This Role, You’ll Use AI To

• Accelerate requirements and backlog quality: convert discovery notes and technical discussions into clearer epics, user stories, acceptance criteria, and test cases—then validate with 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 risks—validated against source systems before sharing.

Why Join / What We Offer (only if I provide the elements; otherwise keep generic and short)

You’ll be part of a new, dedicated AI team with the mandate to deliver real customer value quickly—building the operating model for how InvoiceCloud ships AI responsibly and at scale.

Location / Travel

• Location model: Hyderabad (office-based)
• Travel: Minimal; not expected

InvoiceCloud is committed to providing equal employment opportunities to all employees and applicants. We do not tolerate discrimination or harassment of any kind based on race, color, religion, age, sex, nationality, disability, genetic information, veteran or military status, sexual orientation, gender identity or expression, or any other characteristic protected under applicable laws.

This commitment applies to all aspects of employment, including recruitment, hiring, placement, promotion, termination, layoff, recall, transfer, leave, compensation, and training.

If you require a disability-related or religious accommodation during the application or recruitment process, and wish to discuss possible adjustments, please contact jobs@invoicecloud.com.

Click here to review InvoiceCloud’s Job Applicant Privacy Policy.

For recruitment agencies: InvoiceCloud does not accept unsolicited resumes from agencies. Please do not forward resumes to our job aliases, employees, or any other company location. InvoiceCloud is not responsible for any fees associated with unsolicited submissions.