Embedded Transformation Engineer

Redesign Health•New York, NY

10d

About The Position

Redesign Health is hiring an Embedded Transformation Engineer to lead hands-on technical implementations within healthcare organizations. The role combines the ownership and technical execution of a startup engineer with the ability to build relationships with healthcare practitioners and ensure solutions address real clinical or operational problems. Working alongside healthcare leaders and operators, the engineer brings advanced AI expertise to architect, shape, and implement solutions using the best available technologies. Embedded Transformation Engineers work directly inside hospitals, payers, and healthcare services companies, staying involved beyond strategic advice or pilots to help make solutions part of everyday operations. Work can span EHR and payer integrations, clinical workflows, patient engagement, revenue cycle management, analytics, document automation, and AI systems with suitable evaluation, controls, and security. The role focuses on adoption, trust, and workflow fit, as well as technical capability. The engineer assesses whether to deploy an existing product, adapt a proven solution from the company’s portfolio, or build something new; develops implementation plans; and delivers against agreed scope, milestones, dependencies, risks, and acceptance criteria. They use autonomous coding agents with appropriate harnesses, guardrails, tests, and evaluations; adapt implementations to customer environments; and work within security and compliance requirements, including awareness of PHI and HIPAA. They also enable customer engineers to work effectively with agents and help end users gain confidence through training, pilots, office hours, and feedback loops. NYC is strongly preferred. Compensation varies by background and location and includes portfolio equity.

Requirements

Daily, practical use of autonomous coding agents for production work, with concrete examples of shipped work, verification, and lessons learned.
Judgment to recommend whether to deploy, port, or build a solution and explain the recommendation to skeptical nontechnical stakeholders.
Experience integrating with complex, messy, or poorly documented systems, such as EHRs, payer systems, or legacy stacks.
A track record of delivering against implementation plans the candidate developed, including scoping, sequencing, managing dependencies, and reporting status honestly without close management.
Experience teaching or mentoring engineers in new ways of working.
Ability to earn trust as an outsider through humility, respect, empathy, and collaboration.
Comfort working as one half of a two-person dyad with a non-engineering counterpart who owns the problem definition and stakeholder relationship.
Ability to communicate with operators, CIOs, and CISOs, and translate between their concerns and engineering teams.
Experience with HIPAA-compliant clinical workflows and data models, including areas such as decision support, transcription, medication ordering and reconciliation, and diagnostic results management.
Familiarity with delivering high-velocity product work through a modern agentic coding ecosystem or harness.
Ability to remain engaged with users after go-live and distinguish between software being shipped and actually being adopted.

Nice To Haves

Healthcare systems exposure, such as EHRs, payer and claims data, prior authorization, revenue cycle, scheduling, pharmacy/PBM, or clinical data. Candidates without healthcare experience may still be considered if their agent-orchestration, delivery, and enablement evidence is exceptional, though a ramp period should be expected.
A startup-generalist, consulting, or prior forward-deployed-engineer background.
Experience building or running an internal AI-enablement or developer-productivity program.

Responsibilities

Stay current on agent platforms, coding agents, evaluation and observability tools, and integration tools, and change tools when better options emerge.
Study real workflows with clinicians, revenue-cycle staff, hospital IT, and other practitioners before recommending a solution.
Advise the Field CTO whether to deploy an existing product, port an established portfolio solution, or build something new; recommend and commit to a direction.
Create implementation plans covering scope, modules, milestones, dependencies, risks, and acceptance criteria, and deliver against them.
Raise deviations from plan early and propose options such as descoping, resequencing, workarounds, additional help, or a revised date.
Use autonomous coding agents to deliver work by defining scope, creating harnesses and guardrails, running agents in parallel, verifying results with tests and evaluations, and recovering when work goes off track.
Make implementation and architecture adjustments within the agreed design to fit the customer’s data model, authentication, interfaces, and deployment environment.
Enable customer engineers to work effectively with agents and operate coding and code-review harnesses while maintaining quality.
Train users and run office hours, pilots, and feedback loops until users trust and can operate the solution independently.
Build within customer security and compliance requirements, with PHI and HIPAA awareness.
Partner closely with a non-engineering counterpart who owns the problem definition and stakeholder relationship.
Work with customers and practitioners respectfully to build credibility, understand existing workflows, and support adoption.