Senior AI Engineer
Posted Today by Totaljobs
£700 Per day
Outside
Hybrid
City of London (EC1)
Summary: The Senior AI Engineer role involves designing, building, and deploying production-ready GenAI applications and multi-agent systems within secure environments. The position requires expertise in AI orchestration and cloud-native engineering, particularly with Kubernetes. Candidates must hold active UK Developed Vetting (DV) security clearance. This is a contract position with hybrid and remote work options available in the UK.
Key Responsibilities:
- Design, implement, and optimize multi-agent frameworks and stateful LLM applications.
- Containerize, deploy, and scale AI models, APIs, and microservices across production Kubernetes (K8s) clusters.
- Configure K8s workloads for high availability, managing resource limits, GPU provisioning, and autoscaling for heavy LLM inference workloads.
- Build robust, clean Python codebases that comply with strict data security and air-gapped environment protocols within containerized environments.
- Establish monitoring, evaluation, and CI/CD pipelines specifically for tracking LLM latency, cost, and hallucination rates.
Key Skills:
- Extensive experience managing, scaling, and debugging containerized workloads inside Kubernetes.
- Deep, hands-on experience using LangChain and LangGraph to build complex, stateful, and cyclic agent architectures.
- Strong proficiency in Python, framework integrations (LlamaIndex, Hugging Face), and vector databases (e.g., Pinecone, Qdrant, Milvus, Chroma).
- Background in solid software engineering practices (Git, testing, design patterns, API development via FastAPI/Flask).
- Experience deploying to secure cloud environments (AWS, Azure, or GCP) utilizing standard K8s distributions (EKS, AKS, GKE).
- Hold active DV clearance (SC minimum) and willing to go through DV if chosen.
Salary (Rate): £700 / day
City: City of London
Country: UK
Working Arrangements: hybrid
IR35 Status: outside IR35
Seniority Level: Senior
Industry: IT
Senior AI Engineer (Contract)
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).
- Clearance Requirements: Hold active DV clearance (SC minimum) and willing to go through DV if chosen.