FlatGigs is hiring on behalf of a confidential enterprise banking client undergoing a large-scale Trade Transformation initiative powered by Generative AI.
We are looking for high-impact engineers who can design and deploy enterprise-grade Agentic AI systems integrating LLMs with secure structured private data environments.
This is not a research role.
This is production engineering inside regulated enterprise systems.
Immediate joiners are strongly preferred.
Role Overview The AI Engineer will design, build, and deploy advanced multi-agent AI systems embedded within enterprise trade platforms.
The role requires strong full-stack engineering capability combined with deep expertise in: Agentic AI architectures LLM orchestration Secure enterprise integrations Prompt engineering Vector search systems Key ResponsibilitiesAgentic AI & LLM Architecture Design and implement end-to-end multi-agent workflows Connect LLMs with structured private enterprise data Build modular AI agents with reasoning and tool orchestration Ensure explainability and traceability in regulated environments Prompt Engineering & Reliability Design and optimise advanced prompt frameworks Build guardrails and fallback logic for enterprise stability Implement evaluation frameworks to measure hallucination and output consistency Full Stack Engineering (Node.
js / React) Develop scalable backend services using Node.
js (Express / NestJS) Build secure frontend applications using React + TypeScript Develop RESTful APIs exposing AI workflows Embed AI modules into enterprise trade systems Secure Enterprise Integration Integrate GenAI services using secure API frameworks Implement role-based access control Ensure compliance and sensitive data handling standards AI Tooling & Frameworks Build using LangChain / LangGraph for multi-agent orchestration Implement memory layers and workflow graphs Work with vector databases (Redis preferred) Design and optimise RAG (Retrieval-Augmented Generation) pipelines Required Qualifications 5+ years of full-stack software engineering experience Strong hands-on experience with Node.
js and React Proven experience building LLM-powered production systems Experience designing multi-agent AI workflows Strong understanding of vector databases (Redis preferred) Experience building secure AI systems in regulated domains Preferred Experience Trade Finance / Treasury / Capital Markets exposure Model evaluation frameworks or LLMOps exposure Containerisation (Docker / Kubernetes) CI/CD pipeline integration AI governance and data compliance understanding Ideal Candidate Profile Builder mindset Enterprise-grade engineering discipline Comfortable working in high-security environments Able to ship production AI, not just prototypes