Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.
Must have skills : Program Project Management
Good to have skills : AI & Data Solution Architecture
Minimum 12 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary: Minimum 2 years'' experience in below skill
The platform is not a feature ?? it is a foundational platform that three pilot workstreams will build on from Sprint 1. The Product Owner sits at the intersection of the platform team and all three pilots, ensuring the right things get built in the right order and that DAT stakeholders can see and trust the progress.
This role requires someone who understands enterprise software and data systems well enough to write precise acceptance criteria, prioritize real trade-off reasoning, and represent the program to leaders who are approving budget and access.
Responsibilities
Own and maintain the backlog across all four delivery phases with clear prioritization rationale for every sprint
Define and own the Definition of Done for each phase gate coordinate sign-off with DAT technology stakeholders
Lead sprint planning, backlog refinement, and retrospectives keep velocity visible and impediments escalated quickly
Act as the primary DAT stakeholder liaison: translate enterprise priorities into delivery requirements and surface trade-offs early
Coordinate the three pilot workstreams ?? AI Productivity (PM), AI First Change (SDLC), AI First Run (Ops) ?? ensuring pilots consume outputs and feed requirements back into the backlog
Drive Mobilization: coordinate tech stack approval submissions across AWS services, open-source frameworks, and third-party SaaS vendors track and escalate blockers
Write acceptance criteria for agent capabilities, retrieval quality, HITL approval UX, and observability dashboards
Own demo preparation and stakeholder progress communications run sprint demos connecting technical delivery to business value
Maintain the program risk register own the RACI and escalation paths
Identify and unblock dependencies between the platform team and DAT embedded support groups: Cloud Engineering, Security/IAM, and Legal/OSS review
Required skills
Proven product ownership on enterprise data or AI/ML platforms ?? understands what a graph database, vector store, and LLM agent do at a functional level
Backlog management: Jira or equivalent can write epics, stories, and acceptance criteria at a precision level that engineers can build to without ambiguity
Agile delivery: sprint planning, velocity tracking, retrospectives, and impediment removal in a small, high-accountability team
Enterprise stakeholder management: comfortable presenting to technology leaders, negotiating scope, and managing expectations under pressure
AWS and cloud fluency understands what is being built well enough to assess complexity and hold trade-off conversations with engineers
Data platform literacy: familiar with ETL/ELT pipelines, entity resolution concepts, API integrations, and structured vs unstructured data
Risk and dependency management: live risk register, cross-team dependency tracking, proactive resolution
Communication: can write executive-ready program updates and facilitate demos for technical and business audiences alike
Vendor and approval coordination: experienced navigating enterprise procurement, OSS license review, and vendor risk management
Comfort with ambiguity is net-new can structure work without waiting for perfect specifications
Qualification 15 years full time education
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