Zensar Technologies—Product Specialist

Job description

Description: PRODUCT SPECIALIST Agent-ready specifications and end-to-end quality ownership in a three-person AI-native delivery squad Role Product Specialist Function AI-Native Delivery Squad — Product & Quality Experience 8–12 years, including 3+ years in a combined specification and quality-ownership role Location [Location] — hybrid, with overlap into client business hours Engagement Full-time · small-squad delivery on a fixed-timeline platform build Reports to Delivery Lead / Architect-Orchestrator About the role We deliver platform builds with small AI-native squads. Instead of a large team writing production code by hand, a three-person squad specifies the work, programs and supervises AI coding agents, and verifies everything those agents produce. The agents are the workforce; the squad orchestrates and assures. The Product Specialist owns what gets built and whether it is right. You turn business and partner requirements into specifications precise enough for an agent to implement without ambiguity, then accept the resulting output against intent before the squad ships it. You also own functional, integration and end-to-end quality for the platform. There is no junior tier and no layer of people writing tickets beneath you. Every specification you write is executed at speed, and every gap in it surfaces within hours. This role suits someone who writes with precision, is comfortable saying an increment is not acceptable, and wants to work at the front of AI-assisted delivery rather than read about it. Key responsibilities Specification ownership - Convert business, partner and regulatory requirements into agent-ready specifications — user need, acceptance criteria, API contracts, state transitions, data models, edge cases and negative paths — with no ambiguity left for an agent to resolve on its own. - Own the baseline product specification, the journey and state-machine models, and the acceptance-criteria specification set that serve as executable input to AI coding assistants. - Build and maintain a spec-driven backlog, groomed continuously to stay ahead of agent throughput on a compressed delivery timeline (single-week discovery, multi-week AI-assisted build). - Own requirement traceability end to end — requirement to specification to build to test to sign-off — and produce the traceability evidence pack used at each quality gate. - Specify partner integration contracts alongside the architect: request and response schemas, webhook payloads, callback semantics, error and retry behavior, idempotency rules and correlation identifiers. Accepting and governing agent output - Accept AI-generated output against intent before the squad ships. Decide per increment whether output is fit to ship, needs rework, or must be rejected. - Diagnose specification weakness when agents drift — tighten the specification rather than patch the output. - Work inside defined agent autonomy boundaries, escalating anything that touches personal or sensitive data, consent wording, authentication and session handling, or third-party partner integrations to human decision. - Contribute to the reusable specification, prompt and playbook library so that patterns proven on one journey are reused across the next. Functional, integration and end-to-end quality - Own functional, integration and end-to-end test coverage for the platform — this is a specification-and-quality role, not a pure product role. - Design and execute business-rules validation, partner contract and integration testing (schema validation, webhook signature handling, retries, idempotency, correlation IDs), end-to-end journey testing and negative-path coverage. - Apply AI-enabled test tooling across the lifecycle: requirement intelligence and gap detection, AI test-case generation, AI-powered API automation, and browser automation via Playwright or an equivalent MCP-driven tool. - Coordinate non-functional test coverage — resilience, disaster recovery, accessibility and observability — and manage handover of load and security testing where the client owns those activities. - Drive the quality gates: build-ready, integration-ready, UAT-ready and go-live-ready. Own the evidence that each gate has been met. - Produce quality reporting the squad and client act on — defect clustering, coverage against traced requirements, and release-confidence and stability summaries. Client and partner engagement - Run demos, backlog re-prioritisation and specification traceability reviews with client and partner leads on a fixed cadence. - Join weekly architecture and integration checkpoints with third-party partner engineering teams; drive resolution of contract and schema issues to a decision. - Own client validation of acceptance criteria and secure formal UAT sign-off. - Support go-live readiness, handover documentation and warranty-period defect triage. Must-have skills and experience - 8–12 years across product ownership, business analysis or QA leadership, with at least 3 years in a role combining specification ownership with hands-on quality ownership. - Demonstrable ability to write specifications precise enough to drive automated implementation: acceptance criteria in Given/When/Then form, state machines, data models and API contracts. - Hands-on with OpenAPI/Swagger — able to read, review and specify REST contracts, webhook payloads and error contracts without needing an engineer to interpret them. - Strong integration testing background against third-party APIs: schema validation, webhook verification, retry and idempotency behaviour, correlation and reconciliation of asynchronous events. - End-to-end test design and hands-on automation exposure with Playwright, Cypress or an equivalent framework. - Working fluency with AI coding and testing assistants (for example Claude or GitHub Copilot) as everyday delivery tools — including prompt discipline, context management and disciplined verification of generated output. - Experience delivering in regulated, privacy-sensitive environments with explicit consent capture, data minimisation, masking, role-based access control and audit-trail obligations. - Experience with conversational or messaging-channel products — WhatsApp Business Platform or an equivalent channel via providers such as Infobip or Twilio. - Comfortable operating in a small squad with no junior tier, taking direct accountability for scope, quality and sign-off. - Excellent written English. Much of the deliverable in this role is precise prose. Good to have - Azure exposure — Azure SQL Database, Blob Storage, Key Vault, Azure Monitor and Application Insights, OpenTelemetry-based tracing. - Enough familiarity with Node.js, NestJS and TypeScript to review generated code and reason about workflow and state orchestration — you are not expected to build it. - OCR and document-extraction workflows, including user correction flows for low-confidence extractions. - Experience with spec-driven or agent-based delivery practices — engineering guardrail files, MCP context servers, prompt and skill libraries, human review gates. - Domain background in regulated consumer services — healthcare services, insurance, financial services or similar. - Certification such as CSPO, CSM, or ISTQB Advanced. What success looks like - Discovery week: baseline product and technical specifications, state and data models, acceptance-criteria specifications and the spec-driven backlog are signed off, and agent guardrail guidance is agreed. - Build phase: specifications stay ahead of agent throughput; integration and end-to-end coverage tracks each increment as it lands; build-ready, integration-ready and UAT-ready gates pass on schedule with traceable evidence. - Release: UAT sign-off secured, traceability and hardening evidence pack complete, handover and knowledge-transfer documentation accepted by the client. How we work - Throughput is measured in increments shipped and verified, not story points estimated. - Status, velocity and progress reporting are largely generated — you spend your time on specification and verification, not on administration. - Verification is the core skill. The squad ships only what it can verify, and every merge and release is a human decision. - Design system, platform engineering and engineering management are shared functions across squads rather than embedded in the squad.