Job Description: AI Product Owner

SUMMARY OF ROLE

The AI Product Owner will serve as the connective tissue between Engineering and Delivery teams within Consero's AI Platform. In this role, you will translate business and operational data needs from the Finance& Accounting (F&A;) delivery organization into exact, engineering-consumable specifications. You will own the interface contracts that govern how AI-powered skills consume data, ensuring both teams can build concurrently and with confidence. This is a highly cross-functional role requiring deep F&A; domain expertise, strong technical literacy, and the ability to eliminate ambiguity at the seam between data infrastructure and intelligent application delivery.

JOB RESPONSIBILITIES

Product & Interface Ownership

Author and maintain the Interface Contract the binding specification that defines how AI skills consume data from the underlying data platform.

Own the Field Registry: cataloguing data fields, types, freshness SLAs, source systems, and sensitivity classifications.

Translate Delivery team data requirements into engineering-consumable specifications, confirming completeness before any infrastructure build begins.

Define tool interface standards: naming conventions, schemas, calling patterns, and output contracts for each skill domain.

Cross-Functional Coordination

Drive the Interface Contract Gate — the mandatory alignment checkpoint before parallel builds begin — facilitating sign-off across Engineering, Delivery, and Product.

Serve as the single source of truth at the integration seam, proactively surfacing blockers and proposing resolutions before they stall delivery.

Version and maintain the machine-readable contract standard across all active skill domains.

Coordinate architecture decisions (e.g., Claude Apps vs. Claude Agents)



and manage their downstream impact on data contracts.

Skill Library & Roadmap

Maintain and prioritize the Skill Library roadmap,balancing use case demand against platform readiness and delivery capacity.

Apply F&A; domain knowledge (GL, month-end close, AP/AR, revenue recognition, SOX/GAAP/IFRS) to validate skill data requirements and challenge specs that won't hold up in production.

What Success Looks Like

30 days: Internalize the platform architecture, map all skills to their data dependencies, draft your first Interface Contract, and walk Engineering and Delivery through it.

60 days: Lead the Interface Contract Gate for one live skill. Translate Delivery data requirements into engineering specs with no lost-in-translation loops. Begin maintaining the Field Registry.

90 days: Engineering and Delivery are building concurrently against a contract you authored. Ship one skill from Interface Contract to Integration Gate with a measurable F&A; workflow improvement.

6–12 months: Both Engineering leads and Delivery Operators identify you as the single source of truth for the integration layer. The Interface Contract standard is versioned, respected, and reviewed by both teams.

QUALIFICATIONS

Required:

- Overall 15+ yrs of experience with 8–10 years of product management experience; 5+ years in Finance, Accounting, or FinTech domains




- Proven ability to write precise interface or API-style specifications that engineering and business teams both trust and can act on.
- Solid understanding of F&A; workflows, accounting principles, and ERP ecosystems (NetSuite, Rillet, Sage Intacct).
- Hands-on experience with AI tools (Claude, ChatGPT,Copilot) with a conceptual understanding of how large language models calltools and consume data.
- Strong communication skills — able to write sharp technical specs for engineers and crisp summaries for business stakeholders.

Preferred

- Prior experience in FP&A;, accounting, or audit before transitioning into product management.
- Familiarity with LLM orchestration patterns: tool use, context windows, data sensitivity, and hallucination guardrails.
- Experience with API design, data schemas, prompt engineering, or AI orchestration tooling.

CORE COMPETENCIES

Architecture Literacy — Reads and reasons about multi-layer AI platforms; understands the downstream impact of every contract decision.

F&A; Domain Knowledge — Applies real accounting knowledge to spot logic gaps in data requirements and challenge specs that won't hold at month-end.

Specification Precision — Writes interface contracts that eliminate ambiguity and remove lost-in-translation loops between engineering and delivery.

Cross-Functional Trust — Earns credibility with both engineering leads and delivery operators; viewed as the integrating seam, not a bottleneck.

AI Product Fluency — Designs for LLM tool-use patterns; understands data sensitivity, context limits, evaluation frameworks, and guardrail requirements.

Bias for Clarity — Default response to ambiguity is a structured document, not a meeting. Turns open questions into versioned artifacts.

📌 AI Product Owner (Bengaluru)
🏢 Syncro Squad
📍 Bengaluru