Head of AI Engineering & Enablement

About this role

Tebra only initiates contact with candidates via email from an official Tebra email address (@ tebra.com , @ patientpop.com , or @ kareo.com ) or through our applicant tracking system, Greenhouse. We will only ask you to provide sensitive personal information through our official application portal — not via social media or text message. We do not conduct interviews via instant messaging.

About the Role

We are hiring a hands-on player coach to lead AI across how Tebra runs as a company. You will be building alongside a small team of one to two engineers while simultaneously leading process re-engineering engagements with functional leaders. You will ship code, design agents and re-engineer workflows, while also leading the team around you. With a small team, this role will focus on our internal operations — not the AI in our product. It covers how every function works, how fast we move, and how much leverage each person has. As we scale toward $300M+ in ARR, the goal is to decouple growth from headcount and build an operation that runs leaner as it gets bigger.

Most of the value comes from re-engineering the work itself, so you will pair deep engineering and applied AI skill with strong business judgment and a relentless focus on outcomes.

Your Area of Focus

AI Strategy & Use Case Discovery

• Work with the CEO, CFO, and CPO to identify where AI can drive the greatest efficiency and operating leverage across the organization, and prioritize accordingly.

• Audit and re-engineer business processes before automating them, so we improve how the work is done and not just how fast it runs.

• Build and maintain an AI Opportunity roadmap that prioritizes use cases by ROI, feasibility and strategic impact in partnership with the functional leaders.

Build the Hardest Workflows

• Perform deep-dive assessments to identify the highest-impact efficiency opportunities across all operating functions — then build them, don't just document them.

• Design and build high-value internal agents and automations that address the hardest problems inside our operating functions. Stay hands-on in the build yourself; this is not a role where you commission others and review outputs.

• Own the shared patterns for retrieval, agent design, and secure system-of-record connectivity — including MCP servers, agent-to-agent orchestration, and API integrations — with permission-aware access across Gong, Salesforce, NetSuite, Snowflake, Slack, and Workato.

• Design multi-agent systems where specialized agents hand off to each other across workflow steps, not just single agent automation.

• Build and maintain the organizational context layer, the connective tissue that makes Tebra queryable; meeting capture, knowledge connectors, MCP servers into our core systems and permission aware retrieval so agents and people have a single source of truth.

• Develop and maintain a library of reusable skills, frameworks, and how to guide, allowing one person’s breakthrough workflow scale to the entire organization and the programs compound over time.

• Own the full lifecycle from rapid prototyping to production-grade deployment, including monitoring, evaluation frameworks, error handling, and iteration based on real usage data.

Governance

• Define the approved tools, data-handling rules, build standards, and a shared reference architecture for AI across Tebra's operating functions, in partnership with Legal and Security.

• Own how agents are deployed and monitored once live, ensuring full HIPAA compliance and strict adherence to our data privacy and security policies for PHI, without slowing teams down.

• Stand up an AI risk register, acceptable use policy, and audit trail standards for all production agents, and maintain them as the tooling landscape evolves.

Enable the Functions

• Partner with each function to find high-value use cases and help them build and ship the more routine, accessible agents themselves.

• Coach AI owners inside each function, and run enablement and fluency programs so adoption scales beyond the central team.

• Build genuine on-ramps for less-technical teams: role-specific training, prompt libraries, office hours, and ready-to-use templates that make AI approachable across every level of the org.

• Continuously identify emerging AI tooling, methodologies, and agent frameworks — evaluate new models and techniques to keep Tebra ahead of the curve.

Your Professional Qualifications

Technical Foundation

• 8+ years in software engineering, applied AI, or technical product roles, with a meaningful stretch spent hands-on and building in production — not directing from a distance.

• An engineering background you still use. You can read and write code and ship production systems, not only manage people who do.

• Deep applied AI experience designing and deploying multi-agents systems, RAG pipelines, agent-to-agent orchestrations, MCP servers, and API integrations into systems of record, and LLM-based workflows in production.

• Hands-on experience shipping AI in a HIPAA-regulated or comparable environment — working within BAAs, maintaining audit trails, and keeping PHI out of non-covered tools.

Business & Operational Judgment

• A track record on operationally focused technology projects — workflow automation, systems integration, internal tooling — that demonstrably changed how a business runs.

• Strong business acumen. You can sit with a function leader, understand their workflow end-to-end, and translate it into the right automation — including knowing when the right answer is to redesign the process first.

• A process re-engineering instinct, with the judgment to fix the work before automating it.

Change Leadership & Adoption

• A proven track record of driving adoption and behavior change within non-technical teams — not just shipping the tools, but building champions, running training, and sustaining usage until it becomes a habit.

• Experience leading a small team and coaching others

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