Job Description
Build agentic AI for industries where decisions truly matter - from healthcare to aerospace
Ready to create AI agents that solve real-world challenges in regulated environments? Join a well-funded startup developing secure, explainable AI systems for industries where standard approaches fall short.
You'll work as an AI Engineer in the Applied Science team, taking AI models from research to production and integrating agentic AI systems into real applications. This engineering-focused role involves building and deploying AI automation tools that tackle complex industry workflows across healthcare, aerospace, defence, and manufacturing.
Founded by a successful entrepreneur with previous billion-dollar exits, this company has raised $20M+ and is already partnering with Fortune 500 clients in regulated STEM fields. They're assembling a world-class team to create the next generation of secure, transparent AI agents.
The role offers unique technical challenges in agentic systems for enterprise environments, with access to significant compute resources and the opportunity to shape the direction of a fast-growing team in a no-ego culture focused on building working solutions.
Your focus:
- Develop AI-driven reasoning agents and frameworks for automating complex tasks
- Build and optimise RAG (Retrieval-Augmented Generation) pipelines
- Distill and fine-tune AI models to improve reasoning, automation, and decision-making
- Deploy AI models into scalable, production-ready systems using Python and cloud infrastructure
- Collaborate with researchers to operationalise AI advancements into real applications
- Work with complex datasets (proprietary, customer, and synthetic data)
You should have:
- Proven experience building and deploying AI applications (ideally in a startup or fast-moving environment)
- Hands-on expertise with LLMs and agentic frameworks (AutoGen, CrewAI, LangChain, DSPy, or Haystack)
- Strong background in AI-powered automation and orchestration workflows
- Experience with vector databases and retrieval systems (LlamaIndex, FAISS, Pinecone, Weaviate)
- Solid coding skills in Python and familiarity with cloud deployment tools (AWS, GCP, or Azure)
Nice to have:
- MLOps experience and production ML system deployment
- Experience with fine-tuning AI models
You'll receive:
- Competitive base salary: $160K-$230K (negotiable based on experience)
- Up to 20% performance bonus
- Significant options package
- Healthcare (medical, dental, vision)
- 401k with up to 3% match
- 20 vacation days plus 10 sick days with flexible working hours
- Relocation allowance for moves to Florida
You'll be already be based in SF Bay Area or willing to relocate to Miami, Florida, with relocation support provided. The team values clear communication, hands-on building, and collaborative problem-solving in an environment where your work directly impacts the product.
This is an ideal opportunity for an ML Engineer who has built AI applications before and wants to be part of a small, fast-moving team tackling autonomous workflows that solve real problems in mission-critical environments.
Ready to help shape computing intelligence that amplifies human innovation? All applicants will receive a response.