AI Ops Platform Engineer

Skip to main content AI Ops Platform Engineer hackajob London, England, United Kingdom Apply Join or sign in to find your next job Join to apply for the AI Ops Platform Engineer role at hackajob Email or phone Password Show Forgot password? Sign in Sign in with Email or New to LinkedIn? Join now By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy. AI Ops Platform Engineer hackajob London, England, United Kingdom 1 week ago Be among the first 25 applicants See who hackajob has hired for this role Apply Join or sign in to find your next job Join to apply for the AI Ops Platform Engineer role at hackajob Email or phone Password Show Forgot password? Sign in Sign in with Email or New to LinkedIn? Join now By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy. Save Report this job hackajob is collaborating with Barclays to connect them with exceptional professionals for this role.Join us as an AI Ops Engineer, to build and run an enterprise AI Factory within our Card Merchant Services organisation, enabling AI‑driven change across the merchant payments lifecycle. This role focuses on acquiring, risk and fraud, and merchant servicing, delivering a secure, scalable, and well‑governed AI platform that operates effectively in a highly regulated payments environment.You will be accountable for the end‑to‑end operationalisation of AI, spanning model, prompt, and agent lifecycles; deployment and monitoring; guardrails; and cost optimisation, ensuring AI solutions are production‑ready, auditable, compliant, and scalable across merchant payment use cases.You will also be accountable for the end‑to‑end engineering of GenAI and ML platforms, embedding governance, observability and operational resilience by design, hile enabling teams to deploy and run AI solutions with clarity, assurance and accountability at scale.To be successful as an AI Ops Platform Engineer, you should have experience with:LLMOps / MLOps at production scale, operating the full Generative AI lifecycle including models, prompts and agents, CI/CD pipelines, structured evaluation, drift and hallucination monitoring, and controlled, auditable release processes suitable for banking environments.Cloud‑native AI platform engineering on AWS, with hands‑on delivery using services such as Amazon Bedrock for foundation models, agent orchestration patterns, Lambda and Step Functions, alongside demonstrated Python engineering capability and secure microservices and API design.AI governance, observability and cost optimisation, embedding governance by design through policy as code, alignment to model risk framework expectations, lifecycle traceability and audit‑ready evidence,...