AI Engineering Lead, Fella Health

• If you're excited by making healthcare radically more accessible through AI, can build LLM reliable LLM powered apps, and want your work to directly impact people - this role is for you
• You must thrive in intense, high-velocity environments
• Have 6+ years of highly relevant experience in software engineering with a focus on AI and machine learning
• Have strong experience building production applications powered by LLMs. Prompt and context engineering, RAG systems, model fine-tuning and evaluation frameworks
• Possess strong programming skills using Typescript and/or Python
• Have strong experience designing and building modern, customer-facing API’s
• Are comfortable building user-friendly interfaces using React or similar frameworks
• Have experience leading engineering team members

Desirable

• As AI Engineering Lead at Aios Medical, you'll architect our AI-first future
• You'll own the entire AI strategy across our ClinicOS platform, transforming how millions access healthcare through intelligent automation
• You'll work directly with me, Gzim (our Head of Engineering), our CEO (Richie Cartwright) and the rest of the AI engineering team to build AI systems that deliver world-class healthcare at software scale
• This role combines deep technical expertise with strategic vision
• You'll ship production AI while defining our long-term roadmap
• You'll automate clinical workflows, build AI assistants that enhance our providers, and create systems that scale to 100 million patients
• This will be the most impactful work of your career
• You'll build and lead our AI systems across the entire company. We need someone who can ship production AI while keeping it simple, reliable, and actually useful
• You'll work across clinical, growth, and operations - wherever AI can make us 10x better
• Core AI infrastructure: Build a model-agnostic AI platform that lets us switch between OpenAI, Anthropic, and open-source models seamlessly
• Set up robust A/B testing to optimize performance and costs. Create intelligent routing that matches tasks to the right models. Implement comprehensive monitoring and ensure high reliability with proper fallbacks
• AI-powered clinical care: Drive AI adoption across our clinical operating system. Find the manual processes that slow us down and automate them intelligently
• Create AI assistants that make our clinical team more effective. Measure impact rigorously - every feature must demonstrably improve patient outcomes and operational efficiency
• AI-powered growth: Leverage AI to transform our conversion funnel from personalized outreach sequences to AI sales agents that close deals
• Source new tools like AI video generation, voice synthesis, and behavioral prediction models and adapt them to our specific needs & infrastructure. Target human-level conversion rates while removing all manual touch-points
• Data & experimentation: Be genuinely obsessed with data - it should be your default way of thinking. Study our datasets to identify AI opportunities, build lightweight MVPs in days not months, and run controlled tests with clear KPIs
• Create feedback loops that tell us within weeks if something works. Scale winners, kill losers, and always let data drive decisions over intuition

• Apply with:
• Resume
• LinkedIn
• Github