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Senior ai engineer

London
IO Associates
Ai engineer
Posted: 14 June
Offer description

Senior AI Engineer (Contract) Make sure to read the full description below, and please apply immediately if you are confident you meet all the requirements. Rate: £700 / day IR35 Status: Outside IR35 Duration: 6 months (with high likelihood of extension) Location: Hybrid / Remote options available (UK-based) Security Clearance: DV Cleared The Role We are looking for a Senior AI Engineer to design, build, and deploy production-ready GenAI applications and multi-agent systems within secure environments. This role requires a strong hybrid of advanced AI orchestration and robust cloud-native engineering, specifically focusing on scaling workloads via Kubernetes. Because of the nature of this work, you must hold active UK Developed Vetting (DV) security clearance to be considered. Key Responsibilities Agentic Workflows: Design, implement, and optimize multi-agent frameworks and stateful LLM applications. Kubernetes Orchestration: Containerize, deploy, and scale AI models, APIs, and microservices across production Kubernetes (K8s) clusters. Infrastructure & Scaling: Configure K8s workloads for high availability, managing resource limits, GPU provisioning, and autoscaling for heavy LLM inference workloads. Secure Engineering: Build robust, clean Python codebases that comply with strict data security and air-gapped environment protocols within containerized environments. MLOps & LLMOps: Establish monitoring, evaluation, and CI/CD pipelines specifically for tracking LLM latency, cost, and hallucination rates. What We're Looking For Core Kubernetes Expertise: Extensive experience managing, scaling, and debugging containerized workloads inside Kubernetes. Familiarity with Helm charts, K8s networking, storage volumes, and GPU orchestration is essential. GenAI Orchestration: Deep, hands-on experience using LangChain and LangGraph to build complex, stateful, and cyclic agent architectures. Core Tech Stack: Strong proficiency in Python, framework integrations (LlamaIndex, Hugging Face), and vector databases (e.g., Pinecone, Qdrant, Milvus, Chroma). Software Fundamentals: Background in solid software engineering practices (Git, testing, design patterns, API development via FastAPI/Flask). Cloud Infrastructure: Experience deploying to secure cloud environments (AWS, Azure, or GCP) utilizing standard K8s distributions (EKS, AKS, GKE). xxuwjjq Clearance Requirements Hold active DV clearance (SC minimum) and willing to go through DV if chosen.

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