Senior AI Enablement Engineer
Grow TherapySan Francisco$200k – $250kPosted 4 April 2026
Job Description
About Us:
Grow Therapy is on a mission to serve as the trusted partner for therapists growing their practice, and patients accessing high-quality care. Powered by technology, we are a three-sided marketplace that empowers providers, augments insurance payors, and serves patients. Following the mass increase in depression and anxiety, the need for accessibility is more important than ever. To make our vision for mental healthcare a reality, we’re building a team of entrepreneurs and mission-driven go-getters. Since launching in February 2021, we’ve empowered more than ten thousand therapists and hundreds of thousands of clients across the country and insurance landscape. We’ve raised more than $178mm of funding from Sequoia Capital, Transformation Capital, TCV, SignalFire, and others.
The Opportunity:
We are looking for a Senior AI Enablement Engineer to join the Product Infrastructure team at Grow Therapy and help define how AI transforms the way we work across the entire organization. You will design and build the foundational AI infrastructure, tooling, and workflows that enable every department to operate more efficiently and effectively. You will be part of a hub-based team in San Francisco.
Your responsibilities will include building scalable AI systems, partnering cross-functionally with Engineering, Operations, Finance, Legal, and People teams, and driving measurable adoption of AI-powered workflows company-wide.
What You'll Be Doing:
Design and implement Grow's internal AI control plane and tooling ecosystem, including MCPs, AI skills frameworks, and secure connectors to internal systems such as our code, data warehouses, CRMs, finance tools, and internal databases
Build autonomous agents that can solve common classes of engineering problems (feature building, design changes, refactors, tech debt, bug triage, log analysis, etc)
Build reusable, production-ready AI workflows and department-specific copilots that reduce manual effort and accelerate decision-making across teams
Conduct deep workflow discovery sessions with cross-functional partners to identify high-leverage AI opportunities that drive measurable business value
Partner with Security, Legal, and Data teams to ensure all AI infrastructure is compliant, secure, and aligned with data governance standards
Provide documentation, enablement sessions, and feedback loops to drive adoption, and establish metrics to track efficiency gains and platform reliability
You'll Be a Good Fit If:
You have 5+ years of experience in software engineering, platform engineering, or infrastructure roles with hands-on experience building AI-enabled systems (LLMs, skills, MCPs, orchestration frameworks, etc)
You have experience designing and maintaining internal platforms, APIs, or developer tooling and are energized by improving developer experience
You are a strong cross-functional collaborator who can translate business workflows into well-designed technical systems and communicate effectively with non-technical stakeholders
You bring experience with security, data governance, and reliability best practices in production systems, ideally in regulated or healthcare-adjacent environments
You have familiarity with AI agent frameworks, tool/skills registries, MCPs, or experience integrating enterprise systems (CRM, HRIS, finance tools, ticketing systems)
Employment Type: Full Time, Exempt (or Non-Exempt)
Base Compensation: The base compensation range for this position is $200,000–$250,000 USD Annually
This is a hybrid role with the expectation to work onsite from our San Francisco hub location three days per week (Tuesday, Wednesday, and Thursday) and travel 2–3 times per year (e.g., company and department offsites).
The base compensation for this role will vary depending on several factors, including relevant experience, qualifications, and the candidate's working location.
Full Time Employee Benefits:
Comprehensive Health Coverage: Medical, dental, an ... (truncated, view full listing at source)
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