Senior AI Engineer

Responsibilities:
AI-Powered Feature Development: Build LLM-powered features directly into client-facing platforms, including research intelligence tools, natural language query layers, automated summarisation, and agentic workflows that fundamentally change how investment teams work.
Agentic Tooling and MCP Integration: Design and implement MCP-connected data sources, agentic pipelines, and AI orchestration layers using frameworks like Claude Code, LangGraph, Open Claw, Open Code and similar, extending client platforms with live, intelligent data access.
Full-Stack Application Development: Build end-to-end applications tailored to each client's unique portfolio analytics, risk management, and research workflows from backend APIs to responsive frontends.
Backend Services: Design and maintain high-performance APIs using Python (FastAPI or similar) that power client-specific data access, analytics, and AI inference.
Frontend Development: Build intuitive, responsive user interfaces in React that enable investment teams to interact with complex financial data clearly and efficiently.
Data Pipeline Development: Build and maintain ETL pipelines that handle critical financial market data- positions, securities, risk metrics, and research signals with reliability and performance.
Financial Analytics: Implement analytics layers for performance and risk calculations using time-series and linear algebra operations (Pandas, Polars).
Ship Fast, Iterate Often: Deliver working software in compressed timelines, gather direct feedback from hedge fund users, and continuously improve, treating speed and quality as complementary, not competing.
Kubernetes Deployments: Be able to work fluidly with Kubernetes within each client environment to be able to ship fast and reliably.
Requirements:
3+ years of software engineering experience spanning both backend and frontend development.
Fundamental understanding of the agentic loop that is used within most agent frameworks such as Codex, Claude Code, Open Code, Cline, etc.
You understand from first principles how this works.
Strong Python skills with hands-on experience building APIs using FastAPI, Flask, or Django, as well as CLIs with click, argparse, etc.
Frontend development experience with modern frameworks, particularly React.
Solid understanding of RESTful APIs, data modelling, and secure API design.
Experience with SQL and analytical libraries (Polars, Pandas) for computational workloads.
Exposure to cloud platforms (Azure, AWS, or GCP) and cloud-native architectures.
Experience with containerised development (Docker) and deployment workflows.
Passion for AI: Genuine conviction that AI is transforming software, demonstrated through active use of AI tools in your development workflow (Claude, GitHub Copilot, Cursor, or similar) and curiosity about what comes next.
Deep interest in finance: Strong desire to understand how institutional investors, hedge funds, and asset managers think, make decisions, and use technology; you find the domain genuinely compelling, not just a backdrop.

Experience
4-8 yrs