hackajob
AI Ops Platform Engineer
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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, while enabling teams to deploy and run AI solutions with clarity, assurance and accountability at scale.
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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, supported by SRE‑grade monitoring and ongoing optimisation of token usage and compute cost across AI workloads.
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Some Other Highly Valued Skills May Include
- Retrieval Augmented Generation (RAG) and vector database implementation, with practical experience using technologies such as OpenSearch, FAISS or similar to support scalable, production‑ready retrieval workflows.
- Data pipeline engineering, building and operating AI‑ready pipelines using AWS Glue, S3 and related services to support model training, inference and evaluation.
- Advanced observability and reliability engineering, including experience with CloudWatch, OpenTelemetry and established production resilience patterns for AI workloads in critical banking systems.
You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen, strategic thinking, and digital and technology capability, as well as role‑specific technical skills.
This role will be based in London.
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