AI Engineer - GenAI & Agentic Systems

About

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.

Key Responsibilities

• Agentic 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