I am working with a fast growing AI company building an enterprise grade AI workspace used by major financial institutions to produce and validate client ready work. The platform replaces complex manual workflows with automated AI systems that scale across global teams and has grown rapidly with backing from top tier investors.
This role is for engineers who want to build and ship production systems.
You will own core parts of the AI agent infrastructure, including multi agent systems, RAG pipelines, and evaluation frameworks. The work is hands on and production focused, covering backend services, AI infrastructure, and delivery at scale.
What you will do
- Build and deploy backend services and APIs, Python preferred using Django or FastAPI
- Productionise AI features including RAG, agent orchestration, and evals
- Create data pipelines for training, evaluation, and continuous improvement
- Ensure performance, reliability, and security across the stack
- Work closely with founders, engineers, and product teams
- Five plus years of software engineering experience
- Proven experience deploying AI applications into production
- Strong backend engineering skills and database fundamentals
- Experience with cloud infrastructure, Docker, Kubernetes, and CI CD
- Background workers, task queues, and Redis experience
- Familiarity with LLM evaluation, monitoring, and safety
- Degree from a Russell Group university or equivalent top tier academic background, or alternatively extensive engineering expertise with clear, relevant production experience
If you are an Applied or Agentic AI Engineer looking for real ownership and the chance to build core systems from the ground up, this is worth a conversation.
