AI/ML Engineer | Python | LLM Agents | Agentic Workflows | Must have startup experience | NYC
Location: New York, NY (Hybrid — 3 days/week in office)
Package: $180,000 - $280,000 + meaningful equity
Eligibility: Open to candidates with existing work authorization - US Residents Only
🚨 Please only apply if you have ALL of the following 🚨
- Hands-on experience building and deploying AI agents or LLM-powered systems
- Production-grade ML/AI deployment (not just research or modelling)
- Startup or fast-moving VC-backed company experience
- 3+ years as an ML/AI engineer or applied researcher
Join a hyper-growth AI company fresh off a major funding round, building next-generation agentic technology that's transforming a trillion-dollar industry. You won't be building demos here. You'll be deploying agents that interact with the real world - autonomous systems handling complex, multi-step workflows across research, communication, and decision-making - in a platform that's barely scratched the surface of its potential.
This is a zero-to-one role. You'll help shape the architecture, define the roadmap, and build the agent infrastructure that takes this from early traction to industry standard.
Required Background
- 3+ years as an ML/AI engineer or applied researcher
- Proven delivery of production AI/ML systems in real-world environments
- Experience at a VC-backed AI-native startup or fast-moving, reputable tech company
- Strong grounding in CS, mathematics, engineering, or a related technical field
- Able to operate with a founding-engineer mindset - own it, ship it, improve it
- This is not suitable for full-stack or backend engineers without applied AI/ML depth
- Must be comfortable in a fast-moving, high-autonomy startup environment
- Customer interaction is part of the role - you'll work directly with healthcare providers
- High ownership expected - you will design, build, deploy, and iterate at pace
Must-Haves
- Experience building LLM-powered applications or AI agent architectures
- Hands-on with agentic workflows, multi-agent orchestration, or RAG systems
- Startup mindset with a track record of high personal output
- Ability to translate real-world workflow problems into technical direction
- Strong problem-solving and full ownership of systems end-to-end
Bonus Experience
- Reinforcement learning or RL-from-human-feedback experience
- Background in healthcare, insurance, or billing workflows
- PhD in a relevant field (CS, Data Science, ML)
- Open-source contributions in AI/ML tooling
- Past founding engineer or early technical hire
Hands-On Experience With
- Python (backend systems and ML infrastructure)
- Agentic orchestration frameworks (e.g. Temporal, LangChain, or similar)
- PyTorch, Transformers, or equivalent ML tooling
- Deploying and monitoring AI agents in production at scale
What You'll Be Doing
- Design and build the architecture for a multi-agent AI system handling real-world insurance workflows
- Develop specialised agents for denial classification, root cause analysis, policy reasoning, and appeal generation
- Build reusable agent infrastructure and orchestration frameworks across the platform
Quality & Reliability
- Create evaluation frameworks and feedback loops to continuously improve agent performance
- Design prompt engineering strategies and fine-tuning approaches for production use cases
- Translate field insights and customer feedback into technical priorities
- Work directly with billing managers and healthcare providers to understand workflows
- Partner with the engineering team on production infrastructure and monitoring
- Actively contribute to the AI/ML technical roadmap and company direction
What They're Looking For
- A technically sharp, scrappy engineer who moves fast and takes ownership
- Someone who's built real AI systems - not just run notebooks or fine-tuned models
- A builder who thrives in ambiguity and turns customer insight into working product
- An engineer who wants to be one of the first 20 people shaping a category-defining company
If you have the background above and want to build production-grade AI agents that fix one of the most broken systems in healthcare - get in touch for a fast response.