Senior Platform Product Manager, Data & AI
Description
The opportunity CaseWorthy is the unified whole-person care platform for human services. Roughly 1,000 government and nonprofit organizations run their programs on it, and the millions of people those programs serve depend on the data and decisions that move through it every day. Two things make that platform hard to replicate: CaseWorthy CORE, our unified data foundation, and Cara, the AI grounded natively in it and acting through the applications. This role owns both — as products.
What You’ll Own
Cara — the AI. You own Cara as a product: its infrastructure, its family of Assistants, and its roadmap from reactive assistance to guided workflows to agentic automation. This is the majority of the role and where we most need a strong owner.
CaseWorthy CORE — the data foundation. You own the unified data foundation: the lakehouse, the semantic models, and the cross-program data layer that powers reporting, analytics, and every Cara interaction. CORE is read-only by design — the single source of truth Cara is grounded in.
What You’ll Do
Lead the Platform Pod. Set direction and own the operating rhythm for the pod that delivers the platform layer — the Cara, CORE, and Platform Engineering teams — driving its product, engineering, and design work to outcomes. You lead the product managers within the pod: define the PM standards, rituals, and ways of working, anchored in our Agentic Development Lifecycle (ADLC).
Design the Assistants. Write the specs: the job each Assistant does, its inputs and grounding, its autonomy settings (where a human allows, approves, or pre-authorizes an action), its acceptance criteria, and its guardrails. Every spec anchors to “Cara recommends; humans decide.”
Drive the infrastructure conversation, in partnership. Cara engineering owns the technical infrastructure decisions — model orchestration and routing, retrieval and knowledge grounding across the CaseWorthy University knowledge base, and the evolution from templatized to dynamic querying. You bring the product and cost lens and drive the decisioning alongside them.
Own the MCP and API contract standards. Application teams build and own their MCP servers; you define the shared contract they implement — tool schemas, auth and permission scoping, consent, and the write-boundary rules that keep “Cara recommends; humans decide” intact when agents act through the applications.
Own the unit economics. Partner with Cloud & Data Engineering on a fully-loaded cost-per-use model and design the usage guardrails that keep AI durable at scale. That same cost number both prices Cara and scores what we build next — you own it as a product input.
Set the responsible-AI bar. Define the evaluation, safety, explainability, and human-in-the-loop standards every Assistant clears before it ships — and hold the line on them.
Own CORE as a product — the data foundation, semantic models, ingestion, and the analytics substrate Cara queries, including its role in statewide data-infrastructure engagements. Protect the read-only discipline of the foundation.
Build design patterns that scale. Define reusable Assistant and data patterns that application teams extend by configuration across programs and verticals — build once, scale by configuration.
Partner across engineering. Work with the Engineering organization on the agentic development lifecycle and with the AI Center of Excellence on shared standards.
Prioritize in the open. Run your roadmap through the product prioritization framework, with runtime cost as a first-class input for AI work, and make your decisions visible.
Support go-to-market. Inform pricing and packaging for AI with the cost model and readiness signals — without owning the commercial motion.
Requirements
What success looks like in your first year: A repeatable Assistant design-and-evaluation standard exists, is documented, and is used by every application team shipping AI.
CaseWorthy CORE is the undisputed foundation for analytics and AI across the platform, and is ready to carry statewide data-infrastructure engagements.
The first guided-phase Assistants are specified, in build, and on a credible path — with human-in-the-loop and cost discipline built in from the start.