The role is with a leading Hedge Fund
For AI/LLM Senior engineer: Our requirement is for a seasoned engineer with a strong foundation in distributed systems, data platforms, and application architecture, who has been actively building and deploying AI/LLM-powered agents over the past few years. We are specifically seeking candidates who have demonstrable recent experience designing production-grade agentic systems (e.g., using LangChain, LlamaIndex, Semantic Kernel), integrating multiple heterogeneous data sources, and operationalizing LLM solutions securely within enterprise environments. The emphasis is on depth of architectural capability and current, hands-on AI agent development experience, supported by broader tenured engineering expertise.
seeking a seasoned Senior AI / LLM Application Engineer to design and deploy intelligent, LLM-powered agents that enable business users to query proprietary internal data through natural language interfaces.
This is a hands-on engineering role working at the intersection of applied AI and data engineering, integrating large language models with the firm's Microsoft Fabric data platform and a range of internal data stores. The successful candidate will own the full lifecycle of AI agent development from custom connector design through to production deployment.
The Opportunity
- Design and build custom connectors and AI agents capable of interrogating diverse data stores, including time series databases, document repositories, and relational databases.
- Architect and implement agentic systems using frameworks such as LangChain, LlamaIndex, or Microsoft Semantic Kernel, with full ownership from prototype to production.
- Develop natural language to SQL / DAX pipelines against complex, multi-table financial schemas with robust handling of text-to-SQL failure modes.
- Apply prompt engineering, context window management, and retrieval-augmented generation (RAG) to maximise accuracy and reliability.
- Design agentic systems that enforce row-level security, role-based access control, and data sensitivity classifications end-to-end.
- Integrate LLM APIs (Anthropic Claude, Azure OpenAI) into scalable, production-grade applications deployed on Azure.
Ideal Profile
- 810+ years of progressive software engineering experience, with at least 3 years focused on production AI / LLM application development.
- Proven experience building custom connectors and agents that interrogate multiple data store types time series (e.g. InfluxDB, kdb+), document stores (e.g. Elasticsearch, vector DBs), and relational databases.
- Deep expertise in agentic orchestration frameworks: LangChain, LlamaIndex, or Microsoft Semantic Kernel.
- Strong Python development skills; experience building and deploying API-driven, cloud-hosted applications on Azure.
- Familiarity with Microsoft Fabric, Power BI API endpoints, and Azure cloud deployment patterns.
- Background in capital markets, hedge fund, or asset management environments preferred.
- Exposure to multi-agent system design patterns is advantageous.
Why This Role
- Greenfield AI agent build-out with full architectural ownership.
- Direct exposure to front-office, risk, and data engineering stakeholders.
- Opportunity to define the AI tooling strategy of a global investment firm.
