AI/MLOps Platform Engineer

Join Us in Shaping the Future of AI at Barclays.

We’re launching an exciting new initiative at Barclays to design, build, and scale next-generation platform components that empower developers - including Quants and Strats - to create high-performance, AI-driven applications.

As an AI/MLOps Platform Engineer, you’ll play a pivotal role in this transformation, working hands-on to develop the infrastructure and tooling that supports the full lifecycle of machine learning and generative AI workloads.

This is more than an engineering role—it’s an opportunity to influence technical direction, collaborate across diverse teams, and help define how AI and GenAI are delivered at scale.

To be successful as an AI/MLOps Platform Engineer at this level, you should have experience with:

• Proficiency in Python engineering skills, especially in backend systems and infrastructure.
• Deep AWS expertise, including services like SageMaker, Lambda, ECS, Step Functions, S3, IAM, KMS, CloudFormation, and Bedrock.
• Proven experience building and scaling MLOps platforms and supporting GenAI workloads in production.
• Strong understanding of secure software development,  cloud cost optimization, and platform observability.
• Ability to communicate complex technical concepts clearly to both technical and non-technical audiences.
• Demonstrated leadership in setting technical direction while remaining hands-on.

Some other highly valued skills may include:

•  Experience with MLOps platforms such as Databricks or SageMaker, and familiarity with hybrid cloud strategies (Azure, on-prem Kubernetes).
• Strong understanding of AI infrastructure for scalable model serving, distributed training, and GPU orchestration.
• Expertise in Large Language Models (LLMs) and Small Language Models (SLMs), including fine-tuning and deployment for enterprise use cases.
• Hands-on experience with Hugging Face libraries and tools for model training, evaluation, and deployment.
• Knowledge of agentic frameworks (e.g., LangChain, AutoGen) and Model Context Protocol (MCP) for building autonomous AI workflows and interoperability.
• Awareness of emerging trends in GenAI platforms, open-source MLOps, and cloud-native AI solutions

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, as well as job-specific technical skills.

This role can be based out of our Glasgow or Canary Wharf office.