Overview
Lead Developer responsible for evolving core platform services powering AI-driven products, including backend APIs, LLM pipelines, and agentic workflows.
What you'll do
- Design and maintain back-end services and REST APIs using Python and FastAPI.
- Build and optimize LLM-based extraction, summarisation, and classification pipelines.
- Develop agentic AI workflows with LangGraph, including tool orchestration and reasoning chains.
- Extend and operate an MCP server layer using FastMCP for third-party integrations.
- Design data models and query patterns in MongoDB Atlas for RAG pipelines.
- Build data processing and scheduling pipelines using Apache Airflow on AWS EKS.
What you'll need
- 10–17 years of professional software engineering experience focused on Python back-end development.
- At least 1 year hands-on experience building LLM-based applications (e.g., RAG, agent-based systems, extraction, or prompt engineering).
- Deep proficiency in Python, including modern async frameworks such as FastAPI.
- Strong knowledge of Python packaging, dependency management, and best practices.
- Experience with MongoDB or similar document databases; vector stores/embedding search is desirable.
- Practical AWS experience including containerisation and orchestration such as Docker, Kubernetes/EKS, and Apache Airflow.
- Experience designing production-ready RESTful APIs and contributing to testing, CI/CD, and agile development.
Nice to have
- Experience with FastMCP or the Model Context Protocol (MCP) ecosystem.
- Familiarity with LangGraph or similar agent orchestration frameworks.
- Background processing unstructured data (PDFs, audio, messaging platforms).
- Understanding of capital markets, investment research workflows, or financial data.
- Experience with observability/monitoring tools such as DataDog, Prometheus, or Grafana.
- Degree in Computer Science/Software Engineering or related discipline (or equivalent experience).
Details
Read the full description and apply on the company’s own careers page.
