Job Description

The OTC derivatives market moves trillions of dollars daily on infrastructure that hasn't fundamentally changed in decades. We're building the platform for the next evolution of financial services.

We're a small team that came from trading, quant, and engineering roles at tier one financial institutions who were previously responsible for creating some of the most innovative products in the market. We are now building a platform which can process the most complex transactions executed across financial markets. We are building this right: delightful experience, modern stack, AI-native architecture.

Our clients are the most sophisticated banks, hedge-funds, and asset managers in the world. The problems are extremely hard, the scale is massive, and we're creating infrastructure that will define how this market operates for decades to come.

We are cloud-native employing serverless compute and IAC by design, with services written in both Python and Java. We leverage the latest foundation models and AI tooling, with a front end based on Typescript / React.

We have a fully automated SDLC utilizing Github, Logfire, Vercel and other technologies for rapid and continuous intraday deployment.

About the Role

In this role, you will build generative AI workflows to increase efficiency across the OTC derivative landscape. You will own our evaluation and context engineering infrastructure, ensuring high-quality, reliable, and explainable model outputs. You’ll work closely with financial engineers and domain experts to design retrieval, grounding, and validation pipelines for complex derivative data. This includes building tools for knowledge extraction from trade documents, enhancing data consistency across trade lifecycles, and integrating AI reasoning into workflows for settlement, valuation, and risk management.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Mathematics, Financial Engineering, or a related field
• This role is based in-person at our NYC office
• Strong proficiency in Python; knowledge of Java is a plus
• Proficiency in prompt engineering and structured output generation (e.g., JSON, Pydantic schemas)
• Experience working with NoSQL databases, such as MongoDB or DynamoDB
• Familiarity with cloud infrastructure and deployment tools (CDK, Terraform) and cloud providers (e.g., AWS, GCP, Azure)
• Strong understanding of traditional and AI SDLC
• Strong understanding of software design principles
• Excellent problem-solving and communication skills

Bonus Qualifications

• Experience fine-tuning or deploying large language models (OpenAI, Anthropic, Gemini, etc.)
• Familiarity with vector databases and retrieval-augmented generation (RAG) pipelines
• Experience building AI agents or workflow orchestration for financial data tasks
• Understanding of OTC derivative data models and trade representations (e.g., ISDA)
• Experience integrating AI systems with financial infrastructure (pricing, settlements, risk, or cashflows)
• Familiarity with LangChain, PydanticAI, LlamaIndex, or similar AI frameworks
• Experience with data extraction from unstructured financial documents (confirmations, term sheets, etc.)
• Strong grasp of model evaluation, hallucination mitigation, and data quality management in production AI systems

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