In this role you will build and operate production AI/LLM services, focusing on scalable cloud infrastructure and reliable deployments. You’ll own problems across development, infrastructure and deployment to improve performance, cost efficiency and observability. You’ll work with modern GenAI tech like RAG, embeddings, and LLMs, shaping how AI services run in production. This role offers increasing technical ownership and potential progression to senior/lead, with flexible remote work options. You’ll collaborate across teams to deliver robust, measurable AI capabilities that power real-world use cases.
Pay / Benefits
Remote work with option to spend time in the office
Responsibilities
Build and operate production AI/LLM services
Design and scale AWS cloud infrastructure
Improve CI/CD, infrastructure-as-code and automated deployments
Develop and debug Python services using FastAPI and Pydantic
Build production RAG pipelines (embeddings, indexing, retrieval, reranking)
Implement monitoring, tracing and observability across AI services
Improve system reliability, performance, compute efficiency and cost
Own technical problems from development and staging through to production
Key requirements
4+ years of relevant engineering experience (or equivalent depth)
Background in ML engineering, MLOps, platform engineering or software engineering
Strong Python development experience
Hands-on experience building and operating systems in AWS
Experience deploying and maintaining production ML/AI services
Good understanding of CI/CD, containers and infrastructure-as-code
Experience with monitoring/observability tools (Grafana, CloudWatch, Langfuse or similar)
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