Build the operating system for patient-centric care

Bond OS is the platform layer for modern care delivery. It connects structured patient intake, longitudinal patient context, provider review, clinic and admin operations, orders, prescriptions, commerce rails, platform APIs, analytics, support workflows, and applied AI/ML into one coherent system.

Healthcare delivery is usually fragmented: intake in one place, clinical review in another, ordering and prescription status somewhere else, operations in spreadsheets, support in tickets, and analytics after the fact. Bond OS is built to make those flows work together: one patient context, clear workflows for every role, durable platform primitives, and intelligent assistance where it improves speed, quality, and safety.

We are hiring a Product Lead to own the roadmap for Bond OS across product surfaces and platform primitives. This is a senior, hands-on product leadership role for someone who can move between client conversations, patient and provider workflows, technical contracts, data models, operational edge cases, AI/ML release discipline, and crisp execution with engineering and design.

Why this role matters

Bond OS is entering a new chapter. The core platform is live, the product surface area is expanding, and the opportunity is to make the system more unified, more patient-centric, more operationally powerful, and more intelligent.

This role will shape how the platform scales: how intake becomes usable clinical context, how providers and clinic teams move through work, how orders and prescriptions are tracked, how clients understand performance, how APIs and permissions become stronger platform primitives, and how applied AI/ML earns its way into high-consequence workflows.

The mandate is clear: turn a powerful care-delivery platform into a sharper operating system.

What you will lead

Bond OS roadmap

Own the product roadmap across the full platform:

• Patient intake, patient portal, and longitudinal patient context
• Provider workflows, review queues, clinical decisioning, and safety review
• Clinic and admin operations, group management, permissions, and oversight
• Orders, prescriptions, catalog, commerce, payments, promotions, and fulfillment handoffs
• Platform APIs, integrations, auditability, data contracts, and status models
• Analytics for operations, outcomes, quality, and performance
• Applied AI/ML across intake, summarization, triage, drafting, operations, and decision-support context

You will set priorities, make tradeoffs, sequence dependencies, and keep the roadmap grounded in client value, patient impact, operational leverage, and engineering reality.

Platform primitives

Define and protect the core primitives of Bond OS: patient, intake, encounter, decision, order, prescription, catalog item, group, role, permission, audit event, status, and AI artifact.

Great product work here makes the platform simpler and more durable. It turns repeated workflows into shared systems, edge cases into explicit states, and client-specific needs into reusable capabilities.

Client and user discovery

Partner directly with clients, providers, clinic/admin teams, operators, support, design, engineering, and leadership. You will watch real workflows, understand where care delivery breaks down, and translate that signal into product decisions.

Discovery should change the roadmap. The goal is not to collect opinions; it is to understand where Bond OS can create measurable leverage for patients, providers, clients, and internal teams.

Applied AI/ML product direction

AI/ML is a first-class part of Bond OS. The first opportunities include assisted intake summarization, missing-data detection, suggested triage priority, provider-facing drafting, operational intelligence, quality analytics, and decision-support context.

You will define which use cases are worth pursuing, what good output means, how model-backed features are evaluated before launch, how humans review or override outputs, how failures are handled, and how performance is monitored after release.

The standard is practical and serious: assistive, evaluated, observable, auditable, human-overseen, and suppressible when confidence or safety conditions are not met.

Product execution and spec quality

Write product specs that engineering and design can execute from. Strong specs should include user goals, role-specific flows, states, API contracts, validation behavior, data requirements, audit/logging needs, i18n requirements, acceptance criteria, rollout plan, and release criteria.

For AI/ML-backed features, specs should also define model inputs and outputs, evaluation criteria, red-team cases, confidence and fallback behavior, human review UX, monitoring, and go/no-go thresholds.

Product operating cadence

Maintain the product source of truth: what is live, what is in flight, what is blocked, what is cut, what depends on what, and what done means. Run a written cadence that gives leadership, clients, and the team clear visibility into decisions, tradeoffs, risks, and progress.

What you will do

• Build and maintain the Bond OS roadmap across patient, provider, clinic/admin, order, prescription, commerce, API, analytics, operations, and AI/ML surfaces.
• Translate client, user, clinical, operational, and technical insight into clear product direction.
• Partner with engineering on API contracts, schemas, state machines, validation behavior, performance, reliability, and integration boundaries.
• Partner with design on high-craft workflows that reduce cognitive load and make complex care operations feel clear.
• Prioritize the smallest valuable slices that improve the platform without creating long-term product debt.
• Lead applied AI/ML product discovery and write the first serious AI/ML PRDs for Bond OS.
• Define release gates for high-consequence workflows, including safety, auditability, permissions, i18n, test coverage, and operational fallbacks.
• Communicate roadmap priorities and tradeoffs to internal stakeholders and, where appropriate, strategic clients.
• Create the product discipline that lets a small, senior team move faster without becoming sloppy.

The kind of person who will thrive here

You are a systems thinker with strong product taste. You can reason from first principles, write clearly, and turn ambiguity into a concrete sequence of work. You are comfortable with product depth: workflows, APIs, data models, permissions, state machines, and edge cases are part of the job.

You care about craft because in healthcare software, clarity is operational leverage. Good hierarchy, clear states, thoughtful defaults, precise language, and reliable fallbacks matter. The best product decisions make the system easier to understand for patients, providers, operators, clients, and engineers.

You are also practical. You can hold a big platform vision while shipping small, high-quality slices. You know how to say yes by sequencing and how to say no by explaining tradeoffs. You can work with a lean team and still build something ambitious.

Experience we value

We care most about judgment, taste, execution, and technical credibility. Strong candidates may bring some combination of:

• 6+ years of product management or product leadership experience, ideally with ownership of complex software from strategy through launch.
• Experience building platform, SaaS, healthcare, fintech, logistics, marketplace, developer-platform, operations, commerce, or other high-consequence software.
• Healthcare, health-tech, telehealth, pharmacy, e-prescribing, care operations, or regulated-data experience.
• Experience working directly with customers or strategic clients and translating their needs into scalable product capabilities.
• Technical fluency: API contracts, schemas, state machines, data models, permissions, validation, integrations, observability, and engineering tradeoffs.
• Strong written communication: PRDs, specs, roadmap memos, technical decision documents, launch plans, and executive updates.
• Experience with AI/ML product development, especially evaluation, guardrails, human-in-the-loop UX, model observability, red-teaming, drift monitoring, and responsible release processes.
• Familiarity with healthcare data standards such as FHIR, SDC, HL7, or LOINC.
• Experience in a small or fast-moving team where product judgment mattered more than process weight.
• Background in engineering, design, data, operations, clinical workflows, or technical product management.

What success looks like

First 90 days

• You understand the Bond OS platform across patient, provider, clinic/admin, order, prescription, commerce, API, analytics, operations, and AI/ML surfaces.
• The product source of truth is accurate, sequenced, and useful to the team.
• You have shipped or materially advanced one meaningful cross-surface platform slice through the real quality bar.
• The next-quarter roadmap has clear priorities, explicit tradeoffs, dependency mapping, and measurable outcomes.
• The first applied AI/ML capability has a serious product plan: use case, eval set, guardrails, human review, logging, fallback behavior, monitoring, and launch criteria.
• Clients, users, engineers, design, and leadership can see how your product decisions make the platform clearer.

First 12 months

• Bond OS feels more unified across patient, provider, admin, operations, and client-facing workflows.
• Intake reliably creates usable downstream context across care, operations, analytics, and AI/ML-assisted workflows.
• Orders, prescriptions, status, and fulfillment handoffs are clearer and more actionable.
• The platform has stronger primitives for permissions, auditability, taxonomy, analytics, and operational visibility.
• Applied AI/ML capabilities are in production or controlled rollout with evidence, oversight, and monitoring behind them.
• Strategic clients experience Bond OS as a more complete, coherent, and extensible care-delivery platform.

How we work

• Platform first: surface work should strengthen shared primitives, contracts, workflows, and data.
• Patient context is the spine: intake, decisions, orders, prescriptions, communications, outcomes, analytics, and AI/ML artifacts should accrue to coherent patient context.
• Small slices, high bar: ship the smallest valuable slice that improves the platform without lowering quality.
• Contracts matter: API behavior, validation, permissions, audit logs, states, and data contracts are part of the product.
• AI/ML earns exposure: model-backed features ship with evaluation, guardrails, human oversight, observability, fallback behavior, and monitoring.
• Written decisions compound: clear product writing keeps a lean team aligned and makes tradeoffs durable.
• Craft is leverage: the product should feel fast, clear, safe, and intentional under real operational pressure.

Hiring process

• Intro conversation focused on platform scope, product judgment, and role fit.
• Product leadership conversation around roadmap, tradeoffs, and client/user discovery.
• Technical product conversation around APIs, data models, workflow states, and execution quality.
• Paid work sample or case discussion using a redacted Bond OS scenario.
• Final conversation with leadership.

How to apply

Send your resume including your LinkedIn profile link. A product artifact is encouraged but not required: a PRD, roadmap memo, technical decision document, launch plan, or case study that shows how you think and write.