The Opportunity:
Welcome to Orchestration Works — Ensemble's bold leap into the future of healthcare innovation.
We're building something big. Orchestration Works is a brand-new division designed to move fast, break barriers, and bring cutting-edge technology like AI and automation to life across the healthcare revenue cycle. This is where ideas don't just get tested — they get scaled. Our mission is simple: transform how we work, deliver next-level results for our clients, and lead the industry into tomorrow.
Why Orchestration Works Exists
Healthcare is changing at warp speed. To stay ahead, we're taking R+D out of the lab and putting it into real operations — quickly, intelligently, and boldly. This new division gives us the freedom and focus to experiment, learn, and deploy innovations that make a measurable impact.
What Makes It Different
- A dedicated R+D powerhouse: A 50-person independent team headquartered in Austin, Texas — built to move at startup speed.
- Real autonomy: Independent leadership, resources, and decision-making authority that lets us innovate without friction.
- A laser focus: Revenue Cycle Management innovations powered by automation, AI, and reimagined processes — including work on advanced Administrative and Clinical Reasoning Models.
- A future-ready mindset: We're here to help Ensemble evolve rapidly while protecting what makes us exceptional.
Why It Matters
The future of healthcare isn't waiting — and neither are we. Orchestration Works positions Ensemble to stay ahead of industry shifts, unlock new performance breakthroughs, and deliver smarter, faster, more reliable results for the organizations we serve.
Position Overview
The Head of Applied AI owns AI application practice for Orchestration Works: the discipline of embedding advanced AI in specific operational and clinical revenue cycle workflows and proving it works on real work. The division of labor is clean — if a capability is reusable across many applications, it is platform work and lives with Ensemble's AI organization; if it solves a specific operational or clinical problem, it is application work and it flows through OW. This role owns the application side of that boundary and is the interface to the AI organization.
OW consumes the enterprise AI Platform — foundation models, ontologies, retrieval infrastructure, training pipelines, and shared agentic frameworks — and pulls it forward through real operational demand. It does not duplicate it, and it maintains no parallel model relationships. Within the platform, OW experiments freely: application patterns, prompts, agent designs, and initiative-specific fine-tuning. The Head of Applied AI sets that practice, leads it hands-on across pods, and ensures every initiative conforms to enterprise AI safety and evaluation standards.
What You'll Own
- AI application practice: The standard for how pods design and build workflow-specific reasoning, prompts, agent architectures, and tool use across the portfolio.
- Applied agentic AI: Application of the platform's shared reasoning and agentic frameworks to prioritized revenue cycle problems — denials, coding, eligibility, prior authorization, and other operational and clinical workflows.
- Initiative-specific fine-tuning and evaluation: Tuning and evaluating models for specific initiatives within the platform's pipelines and evaluation standards.
- Platform consumption, not duplication: Use the AI organization's platform capabilities and drive its evolution through real operational demand — no parallel model relationships, no shadow infrastructure.
- Operator-validated AI: Partner with the Head of Operator Engagement so every AI capability is validated by front-line teammates on real workflow — in shadow, parallel, or controlled production mode — before concept lock.
- Safety and standards conformance: Per-initiative conformance to Ensemble's enterprise AI safety, evaluation standards, and guardrails.
- Technical leadership of pod AI talent: Guide the AI Engineers and Scientists seconded onto each pod; hands-on design, review, and problem-solving.
What You Bring
Required
- 10+ years of AI/ML experience with progressive leadership responsibility, including leading applied AI or ML teams.
- A track record of shipping applied AI products into production — moving teams from experimentation to deployed, measurable business outcomes.
- Deep hands-on fluency with modern AI application patterns: large language models, agentic architectures, retrieval-augmented generation, prompt and context engineering, fine-tuning, and evaluation.
- Experience operating within (or building on) an enterprise AI platform, including evaluation frameworks and safety guardrails.
- Cross-functional leadership across product, engineering, and operations, with the communication skills to influence technical and non-technical stakeholders.
Preferred
- Healthcare or revenue cycle domain experience; familiarity with regulatory and security frameworks (HIPAA, HITRUST).
- Experience designing human-in-the-loop systems or AI that works alongside front-line operators.
- Experience with rigorous model evaluation practices, including adversarial testing and statistically sound offline evaluation.
- Advanced degree in computer science, AI/ML, or a related field.
How We Work at Orchestration Works
- 120 days, three gates: Every initiative moves from intake to deployment-ready in 120 days or less, through three decision gates. Killing a concept at the gate is a legitimate, expected outcome — that is the model working, not breaking.
- Multi-hat, startup-like team: Roles here are broader than their titles. Leaders operate hands-on, pods rotate in and out on initiative cycles, and everyone contributes beyond their lane.
- Validated on real work: Front-line Ensemble teammates use what we build on real workflow before anything is locked. Solutions are designed around validated work, not assumption.
- Built on Core: Same codebase, same CI/CD, same Ensemble engineering bar. OW proves it; Core scales it.
- Co-located in Austin: The dedicated team and active pod members work together in person at the OW office. Candidates must currently reside in the Austin area or be willing to relocate; relocation assistance may be available for eligible candidates.
