Omnis Partners
AI Platform Engineer
Get notified of more jobs like this · No spam, ever
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
AI Platform Engineer – Agentic AI / GenAI
6-Month Contract - Outside IR35
London – 2 Days per Week
We’re looking for an experienced AI Platform Engineer to join a leading enterprise client of ours in London, helping build and mature the platform infrastructure that will underpin the organisation’s growing AI and GenAI capability. This is a hands-on role sitting at the intersection of Platform Engineering, MLOps, LLMOps and Agentic AI.
The business already has strong engineering foundations in place, but as AI adoption accelerates, they are looking to bring in additional production-grade expertise to improve the scalability, observability, governance and reliability of agentic AI systems. You’ll work closely with AI Engineers, Data Scientists, Software Engineers and Product teams to help move AI solutions beyond experimentation and into secure, scalable production environments.
What you'll be doing
- Architect, build and maintain highly reliable infrastructure supporting AI, LLM and agentic workloads.
- Build core AI platform components including LLM gateways, routing layers, evaluation frameworks and shared services.
- Support the deployment of AI agents, RAG applications, APIs and autonomous workflows into production.
- Improve the scalability, reliability, security and observability of the AI platform.
- Build and maintain cloud infrastructure using Terraform / Infrastructure as Code.
- Operate containerised environments using Docker and Kubernetes.
- Develop and improve CI/CD pipelines for AI and software workloads.
- Partner with AI and Product teams to provide tooling and architectural guidance that accelerates the delivery of new AI use cases.
- Help establish engineering standards and best practices for AgentOps, LLMOps and production AI.
- Implement robust monitoring and evaluation of AI applications across quality, performance, latency and cost.
- Work with tooling such as LangSmith, LangFuse or similar AI observability platforms.
- Support integrations with vector databases, graph databases, semantic caches and LLM orchestration layers.
- Help integrate external tools and enterprise systems using modern approaches such as Model Context Protocol (MCP).
- Contribute to the convergence of traditional MLOps and modern LLM / Agentic AI infrastructure.
- Evaluate emerging AI infrastructure tooling and recommend where new technologies can add genuine value.
- Ensure AI systems are built with appropriate governance, security, permissions, auditability and responsible AI controls.
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What we're looking for
We’re looking for a strong Platform Engineer who combines solid infrastructure engineering fundamentals with genuine experience working around production AI systems. You’ll ideally have:
- Strong experience across Platform Engineering, DevOps, SRE, Backend Engineering or ML Platform Engineering.
- Commercial experience supporting production-grade AI, ML or LLM systems.
- Experience taking Agentic AI / GenAI applications beyond POC and into production.
- Strong knowledge of at least one major cloud platform, ideally GCP, although AWS or Azure experience is also relevant.
- Strong Kubernetes and Docker experience.
- Strong Terraform / Infrastructure as Code knowledge.
- Experience designing and maintaining modern CI/CD pipelines.
- Good understanding of LLMOps, AgentOps and/or MLOps.
- Exposure to modern agentic frameworks and orchestration approaches.
- Experience with vector databases, graph databases, semantic search or caching technologies.
- Understanding of AI evaluation and observability tools such as LangSmith, LangFuse or equivalent.
- Knowledge of MCP, APIs and integration patterns for connecting AI agents with enterprise systems.
- Strong understanding of cloud networking, IAM, security, monitoring and observability.
- Python and/or strong scripting experience.
Get help with your application
Your very own career expert that helps elevate your application to the next level.
The ideal profile
You don’t necessarily need to be an AI Engineer or Data Scientist.
We’re particularly interested in Platform Engineers who understand what good production engineering looks like and have successfully applied that rigour to AI and agentic systems. You’ll be comfortable working in environments where requirements are evolving quickly, turning ambiguous problems into scalable platform capabilities while balancing delivery speed, reliability, security and governance.
Experience working on zero-to-one AI infrastructure or platform initiatives would be highly advantageous.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location