AI Java Lead Engineer

Job highlights

• At least 6 years relevant experience would generally be expected to find the skills required for this role. Disclaimer: This job posting has been aggregated from external source

AI Java Lead Engineer - Vice President - Software Engineering

Job Summary

Were seeking someone to join our Institutional Securities Technology (Prime Brokerage AND Institutional Equity) team as a Java Backend Engineer to build scalable, high-performance enterprise applications on a team thats adopting agentic AI workflows (built on frameworks like the Claude Agent SDK). This is fundamentally a backend engineering role - the bar is deep Java/Spring Boot craftsmanship and strong problem-solving. AI/agentic experience is crucial; we need someone who is aware & can quickly pick up orchestrator/subagent patterns & eval workflows.

In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities. This is a Lead Software Engineer position at Vice President Level, which is part of the job family responsible for developing and maintains software solutions that support business needs.

• Hands-on Java development.

• Deep Spring Boot, microservices, REST APIs, messaging integrations (Kafka, JMS, RabbitMQ).

• Strong SQL, concurrency & distributed systems design

• CI/CD, DevOps, production observability.

• Experience in performance tuning and scalability improvements.

• Demonstrated strong problem-solving ability and comfort learning new technologies quickly

  What you ll bring to the role:

• Genuine interest in AI-assisted / agentic software development, with basic hands-on exposure (personal projects, POCs, or production) to LLM-integrated systems - e.g., calling OpenAI/Azure OpenAI/Anthropic APIs, or using tools like GitHub Copilot / Claude Code in a substantial way.

• Ability to grasp and reason about agentic concepts: orchestrator/subagent patterns, tool/function calling, eval-driven iteration ("hill climbing"), and basic prompt engineering.

• Python exposure for AI integration, scripting, or data pipeline use cases.

• Hands-on experience integrating LLMs into production backend systems (OpenAI, Azure OpenAI, Anthropic, or equivalent).

• Working knowledge of agentic AI frameworks - LangChain, LangGraph, Spring AI, AutoGen, CrewAI, or Claude Agent SDK - including agent memory, tool calling, and multi-step reasoning loops.

• Ability to design multi-agent workflows: orchestrator/subagent patterns, agent-to-agent communication, and guardrails for autonomous systems.

• Awareness of AI system reliability concerns: hallucination mitigation, observability (tracing agent runs), latency, and cost management.

• Curiosity and self-driven experimentation with emerging agentic patterns (ReAct, Chain-of-Thought, reflection loops, human-in-the-loop gates).

• RAG architecture and Vector Database concepts.

• Financial Services or Investment Banking domain experience.

• At least 6 years relevant experience would generally be expected to find the skills required for this role.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.