AI Engineer - GenAI & Agentic Systems

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 OverviewThe AI Engineer will design, build, and deploy advanced multi-agent AI systems embedded within enterprise trade platforms.Key ResponsibilitiesAgentic AI & LLM Architecture Design and implement end-to-end multi-agent workflowsConnect LLMs with structured private enterprise dataBuild modular AI agents with reasoning and tool orchestrationEnsure explainability and traceability in regulated environmentsPrompt Engineering & Reliability Design and optimise advanced prompt frameworksBuild guardrails and fallback logic for enterprise stabilityImplement evaluation frameworks to measure hallucination and output consistencyFull Stack Engineering (Node.js / React) Develop scalable backend services using Node.js (Express / NestJS)Build secure frontend applications using React + TypeScriptDevelop RESTful APIs exposing AI workflowsEmbed AI modules into enterprise trade systemsSecure Enterprise Integration Integrate GenAI services using secure API frameworksImplement role-based access controlEnsure compliance and sensitive data handling standardsAI Tooling & Frameworks Build using LangChain / LangGraph for multi-agent orchestrationImplement memory layers and workflow graphs Work with vector databases (Redis preferred)Design and optimise RAG (Retrieval-Augmented Generation) pipelinesRequired Qualifications5+ years of full-stack software engineering experienceStrong hands-on experience with Node.js and ReactProven experience building LLM-powered production systemsExperience designing multi-agent AI workflowsStrong understanding of vector databases (Redis preferred)Experience building secure AI systems in regulated domainsPreferred Experience Trade Finance / Treasury / Capital Markets exposureModel evaluation frameworks or LLMOps exposureContainerisation (Docker / Kubernetes) CI/CD pipeline integrationAI governance and data compliance understandingIdeal Candidate ProfileBuilder mindsetEnterprise-grade engineering disciplineComfortable working in high-security environmentsAble to ship production AI, not just prototypes#J-18808-Ljbffr