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VP, Enterprise GenAI Backend Engineer, Group Technology & Ops
VP-level backend engineer at UOB's Group Technology & Ops building production-grade GenAI applications: agentic workflows, RAG, tool calling and LLM integration with enterprise systems, using LangGraph/LangChain, Python or Java, and Kubernetes/OpenShift. Requires 6+ years software engineering; banking experience not required.
Senior GenAI Engineer – Python
Senior engineer designing and shipping LLM-powered backend services in Python for a Billennium client: building agentic flows, RAG retrieval and tool calling with LangGraph, serving them via FastAPI on Azure, and owning answer quality through evaluations, tracing (Langfuse) and latency/cost optimization.
Full stack Engineer (Python, React, Django, Typescript) - Remote
Full-stack engineer taking features from concept to production at a small product company building AI-powered decision-support software — designing data models, building REST APIs in Python (Django/FastAPI), and shipping React/TypeScript UIs, with LLM feature integration, Docker and cloud.
Gen AI Engineer
Builds production LLM-powered AI agents: developing RAG pipelines, multi-agent orchestration, and agent frameworks in Python, with evaluation, guardrails, observability, and CI/CD. Requires 5+ years in ML/software engineering and 2+ years with LLMs; based in Delhi/NCR at Voireai Consulting.
Tech Lead IA Générative & Agentique (F/H) - CDI
Tech Lead for generative & agentic AI embedded in a client's Data & AI team in Lyon: ~50% hands-on design/development, ~50% architecture and team enablement. Works across the AI lifecycle from POC to production on AWS Bedrock, GCP Vertex AI and Azure Foundry, with MCP-based agent harnesses, model/agent evaluation, CI/CD, guardrails and FinOps cost control.
Product Owner / Business Analyst - Intégration de cas d'usage IA générative RAG - Freelance (H/F)
Freelance Product Owner / Business Analyst (daily rate €500) embedded in a major international banking group's AI center, driving deployment and adoption of RAG use cases on Dataiku: framing business needs, writing user stories, managing the backlog, coordinating stakeholders and supporting users. Tooling: Jira, Confluence, Microsoft 365, SharePoint.
RAG & AI Data Engineer: Build Scalable AI Pipelines
Diagonal recruitment is hiring a data engineer in London to design and build data pipelines supporting AI applications, developing Retrieval-Augmented Generation (RAG) architectures and vector databases. The role focuses on practical AI implementation and reliable data foundations for AI systems.
AI Engineer
Remote AI engineer with 2+ years of software experience building LLM features (drafting, summarising, extraction, tool-using assistants), guarded agent workflows, and evaluation/regression suites for client projects and the company's own products. Works in Python/TypeScript with RAG, model routing, and optionally fine-tuning and on-device inference.
Desenvolvedor(a) python sênior ia
Senior Python developer building generative-AI applications and LLM-based autonomous agents (Agent Harness, Agent Loop, RAG) plus backend APIs for strategic digital-transformation projects at a large multinational insurance client. Stack centers on Python, FastAPI, LangChain/LangGraph, vector databases, Docker and cloud.