AI ML Ops

AI/ML Ops Location - Sheffield Software Engineering Delivery o Design Build and ship production quality services within our current business controls o Build and Optimise DecOps pipelines enhancing CICD processing including testing and platformprocess observability o Design iterate and optimise prompts for a wide range of LLM use cases instruction following structured output generation classification summarisation code generation and reasoning tasks o Build and manage prompt libraries and versioning strategies treating prompts as firstclass engineering artefacts o Collaborate with product and domain teams to translate business requirements into precise wellstructured prompt specifications Agentic AI LLM Integration * Architect and implement maintain agentic systems autonomous agents multiagent pipelines tool use workflows planning loops and memory augmented reasoning * Implement LLM observability logging tracing evaluation pipelines and guardrails to maintain quality and reliability in production AI systems * Advise on responsible AI deployment including output validation human in the loop design and risk mitigation for agentic workflows. Technical Skills Experience FullStack Engineering * Strong proficiency in Java Spring Boot REST APIs eventdriven services security and performance optimisation. * Solid React development skills and API integration * Experience with relational and in memory databases PostgreSQL Redis * Messaging and streaming platforms Kafka or equivalent Prompt Engineering * Demonstrable handson experience engineering prompts for production LLM applications not just prototypes * Familiarity with prompt evaluation frameworks and tooling PromptFlow LangSmith Braintrust or custom eval pipelines * Understanding of tokenisation context limits temperature tuning and modelspecific behaviours across major LLM providers * Experience structuring prompts for toolfunction calling structured JSON output and multiturn conversations DevOps Infrastructure * Kubernetes deployments services ingress Helm Kustomize HPA and RBAC * CI/CD pipelines GitHub Actions Git Lab CI Jenkins or equivalent * Infrastructure as code Terraform * Cloud platforms AWS GCP or Azure Skills Mandatory Skills : MLOPS, Python