Senior Product Associate - Data Management & Data Governance — Data & Analytics Agent Platform

JPMorgan Chase & Co. • Jersey City, NJ

9h • $99,750 - $155,000

About The Position

As a Senior Product Associate in the Data and Analytics team, you will own data management and data governance for the Data & Analytics Agent Platform. This is a hands-on, delivery-led role focused on turning governance processes into working agents, tools, and orchestrations that reduce manual effort. You will work with existing platform APIs and partner with platform teams to create new APIs where required.

You will lead agentic workflows across the full lifecycle, from identifying opportunities and designing workflows to evaluation, production release, monitoring, and iteration. You will establish reusable patterns and tools, define quality and reliability measures, and help other teams build on the platform. You will also ensure that agents respect data classification, entitlements, retention, cross-border constraints, and approved-use boundaries, while meeting governance, audit, and control requirements.

The role involves close collaboration with product, engineering, platform, data office, and business stakeholders, as well as influencing teams without direct authority. Success in the first 12 months is measured by production workflows that demonstrably reduce manual governance effort, reusable patterns adopted beyond your team, platform APIs that enable new workflows, evaluation and monitoring for production agents, and appropriate governance approvals without material data, privacy, or access incidents attributable to your agents.

Requirements

• At least 3 years of experience or equivalent expertise in product management or a relevant domain area.
• Proficient knowledge of the product development life cycle.
• Experience with product life-cycle activities, including discovery and requirements definition.
• Developing knowledge of data analytics and data literacy.
• At least 3 years in engineering, data platform, or technical solution delivery, with recent hands-on experience building LLM-based or agentic applications in production; prototypes or proofs of concept alone are not sufficient.
• Demonstrated ability to build against and integrate with enterprise APIs; practical knowledge of REST and event-driven patterns, authentication and authorization models, and integration failure modes.
• Proficiency in Python or an equivalent language and current agent frameworks and orchestration tooling; comfort with RAG patterns, vector stores, tool and function calling, and multi-agent or multi-step orchestration.
• Experience designing evaluation and monitoring for non-deterministic systems, including offline evaluations, regression testing, guardrails, and production observability.
• Record of influencing platform and engineering teams to build or change APIs, including writing clear technical requirements and contracts.
• Working knowledge of data management and governance concepts, including metadata, lineage, classification, data quality, entitlements, and retention, sufficient to automate processes credibly and engage governance stakeholders as a peer.

Nice To Haves

• Prior experience automating risk, control, or governance processes in a regulated environment.
• Experience in financial services or another industry with comparable data-protection and auditability constraints.
• Exposure to cloud data platforms, Lakehouse architectures, and modern data tooling.
• Familiarity with AI governance expectations and applicable data-protection regulations, particularly in getting systems approved and deployed.
• Experience leading small technical teams or acting as a tech lead on multi-workstream delivery.

Responsibilities

• Partner with the Product Manager to identify product opportunities through user research and discovery.
• Consider upstream and downstream impacts of new product features on the overall product experience.
• Support user research, journey mapping, and market analysis to inform the product roadmap and identify valuable features.
• Analyze, track, and evaluate product metrics, including delivery against time, cost, and quality targets.
• Write requirements, epics, and user stories to support product development.
• Serve as the DMDG platform's primary representative on the Data & Analytics Agentic Platform and design, build, test, and ship workflows automating data management and governance activities.
• Decompose governance processes into agent-executable task graphs, including tool selection, prompt and instruction design, context and retrieval strategy, memory, deterministic versus LLM steps, human checkpoints, and fallback behavior.
• Own the agent lifecycle: prototype, evaluate, harden, release, monitor, and iterate.
• Define evaluation sets and quality baselines before scaling; instrument agents for cost, latency, accuracy, and intervention rate.
• Build reusable patterns, tool libraries, and reference implementations for other teams.
• Map platform APIs to workflows and compose agents and tools over them, addressing authentication, entitlements propagation, pagination, rate limits, idempotency, and error recovery.
• Identify platform capability gaps and partner with platform engineering to define and deliver APIs, including use-case briefs, contracts, schemas, payloads, semantics, SLAs, and workload validation.
• Act as a design partner and first consumer for new platform APIs, piloting early versions and driving improvements to usability and performance.
• Define interim approaches when suitable APIs are unavailable, along with conditions for retiring those approaches, and avoid durable workarounds.
• Run an opportunity pipeline with data office and business stakeholders to identify, size, prioritize, and sequence candidate workflows.
• Partner with Area Product Owners and engineering to incorporate agent work into platform roadmaps and release cycles.
• Lead or coach a small team of engineers and solution builders, set technical direction, and raise agent build quality.
• Report delivery and impact metrics to senior management, including workflows automated, hours displaced, adoption, agent reliability, and cost to serve.
• Apply data management and governance knowledge so agents respect classification, entitlements, retention, cross-border constraints, and approved-use boundaries, and do not widen source-system permissions.
• Navigate AI/ML and data governance reviews, preparing artifacts needed to secure approval and production deployment.
• Ensure agent actions, inputs, and outputs are logged and traceable to standards acceptable for audit and control testing.

Benefits

• Competitive total rewards package, with base salary determined by role, experience, skill set, and location.
• Eligible roles may receive commission-based pay and/or discretionary incentive compensation in cash and/or forfeitable equity.
• Comprehensive health care coverage.
• On-site health and wellness centers.
• Retirement savings plan.
• Backup childcare.
• Tuition reimbursement.
• Mental health support.
• Financial coaching.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed