Director of AI Engineering

As Director of AI Engineering at Parachute Health, you will be a dedicated AI builder. This is a hands-on engineering role, not an advisory or program-management one: you will find the places where AI-native systems can remove operational waste, then personally design, build, and deploy them. You will write production code, wire up agentic systems, and be accountable for systems that are live and running across the organization.

You will lead a small pod of 2-4 engineers that embeds with business functions across the company, ships AI-first solutions, and equips each team to maintain what you've built before moving on to the next opportunity. Your impact will be measured in throughput and leverage gained by those functions.

• →  Design, Build, Harden and Deploy End-to-End: Personally ship agentic solutions from scoping the problem and selecting the right tools through production code, orchestration layers, testing, and handoff to a maintained system.
• →  Own the AI Automation Roadmap: Within a transformation engagement, identify and prioritize automation opportunities within internal operations (supplier onboarding, clinician activation, sales, finance, and support) and sequence a roadmap of the highest-leverage builds.
• →  Lead the Pod as a Player-Coach: You are the first engineering hire of the AI transformation team. Directly manage a team of 2-4 engineers while staying hands-on in the work. Set the pace, hold the code quality bar, and model the velocity standard: days, not weeks.
• →  Turn Problems into Systems: Conduct discovery with internal teams, map current-state workflows, find the highest-leverage intervention points, and design, build, test and hip end-to-end AI-first processes.
• →  Scout the Tooling Frontier: Influence company-wide decisions on new models, orchestration frameworks, agent toolkits, and workflow platforms, and bring the right ones to Parachute's specific operational challenges.

•   Software Engineering Foundation: You understand system design, deployment, APIs, data flow, and the full SDLC, and you apply that rigor to AI systems. You write and ship production code, not just prompts.
•   Agentic Fluency and Engineering Depth: You have hands-on experience with RAG pipelines, vector databases, LLM orchestration (LangChain, LangGraph, or equivalent), voice-agent infrastructure, MCP, and multi-agent coordination. You know when to use each and why.
•   Hands-On Builder: You have personally built and deployed AI-powered systems that drove real operational outcomes, not only managed the team that built them. You can point to concrete throughput or efficiency gains.
•   Bias for Speed and Impact: You ship meaningful systems with speed - fully enabled by the latest AI coding tools.
•   Structured Communicator: You can walk a non-technical stakeholder through what you're building and why it will work, probe their problem to find the real constraint, and translate their feedback into precise technical requirements.
•   Player-Coach: You've built and led small, high-output technical teams. You know how to hire, onboard, and develop engineers while staying in the work yourself.
•   Nice to Haves: Deep ML experience; business transformation and change-management acumen.