Senior AI​/ML Engineer

We have partnered with a rapidly scaling fintech company headquartered in New York that is redefining how mid-market businesses manage financial risk through AI. Series C funded and backed by some of the most respected names in financial services venture, they have grown from 80 to 250 people in the last 18 months and are on a clear path to IPO within the next three years.

Their platform is already trusted by over 400 enterprise clients, and the AI team sits at the absolute core of the product, not as a bolt-on.

This is a senior hire that will shape the direction of their AI capability. As the business accelerates its roadmap, they need an experienced AI/ML Engineer who has been here before, someone who can operate with autonomy, make strong technical decisions, and raise the bar for the team around them. You will be working on problems that genuinely matter, with real data, real stakes, and real impact on the product.

• Architecting and building production‑grade LLM pipelines and RAG systems that power core platform features
• Leading the integration and fine‑tuning of large language models for financial data use cases
• Owning vector database infrastructure including Pinecone and Weaviate to support intelligent search and retrieval at scale
• Acting as a technical authority across the AI team, mentoring more junior engineers and setting engineering standards
• Partnering directly with product and data science leadership to define and deliver the AI roadmap

• 5 to 8 years of hands‑on AI/ML engineering experience
• A strong track record of shipping LLM‑powered products into production at scale
• Deep expertise in Python and frameworks such as Lang Chain or Llama Index
• Solid cloud platform experience across AWS or GCP
• The ability to operate as a technical leader without needing a lot of direction

• Background in financial services or fintech
• Experience with Pinecone, Weaviate, or ChromaDB
• Exposure to financial risk modelling or fraud detection use cases

• Meaningful equity package
• Fully remote‑first with occasional team offsites