AI Platform Engineer reference: 0000083803

Barclays: Pioneering the Future of AI with a Groundbreaking Platform Engineering Opportunity

Barclays is embarking on an exciting and transformative journey to build a next-generation AI platform. This initiative is designed to empower front-office developers, specifically Quants and Strats, by providing them with the tools and infrastructure to create high-performance, AI-driven applications. As an AI Platform Engineer, you will be at the forefront of this innovation, playing a critical role in shaping the architecture, development, and scaling of a robust platform that supports advanced AI/ML workloads. This is a unique chance to influence how AI is leveraged within financial services, impacting both on-premises and cloud environments.

This hands-on engineering role offers the opportunity to directly impact the delivery of secure, scalable, and innovative solutions. You will collaborate with diverse teams, tackle complex technical challenges, and contribute significantly to the technical direction of a platform set to revolutionize AI adoption in the financial sector.

Key Advantages for Potential Candidates:

• Shape Cutting-Edge AI: Be an integral part of building a state-of-the-art AI platform from the ground up, directly influencing its capabilities and future direction.
• High-Impact Role: Your expertise will enable Quants and Strats to unlock new levels of performance and innovation through AI, making a tangible difference in the business.
• Hybrid Cloud Expertise: Gain invaluable experience working with both on-premises infrastructure and a comprehensive suite of AWS services, alongside potential exposure to Azure.
• Deep Dive into Generative AI: Opportunities to work with and integrate cutting-edge generative AI tooling, including Large Language Models (LLMs) and agentic frameworks.
• Career Growth and Influence: This role offers significant opportunities for technical leadership, strategic influence, and mentorship, allowing you to guide engineering teams and shape technical strategy.
• Collaborative Environment: Work within a dynamic, cross-functional team environment, fostering a culture of knowledge sharing and continuous improvement.
• Focus on Best Practices: Emphasis on secure software development, cloud cost optimization, platform observability, and robust testing practices.

Key Considerations for Your Career Path:

• Required Expertise: A strong foundation in Python engineering, particularly backend and infrastructure tooling, is essential. Deep knowledge of key AWS services such as IAM, KMS, CloudFormation, API Gateway, S3, Lambda, ECS, Glue, Step Functions, MSK, EKS, and Bedrock is critical.
• AI/ML Platform Scaling: Proven experience in scaling platforms specifically for AI/ML workloads and integrating generative AI tooling is a must.
• Security and Optimization: Understanding of secure software development principles, cloud cost optimization strategies, and platform observability is vital for success.
• Communication Skills: The ability to clearly articulate complex technical concepts to both technical and non-technical audiences will be key to your influence and effectiveness.
• Advanced Skills (Highly Valued): While not always mandatory, experience with MLOps platforms (e.g., Databricks, SageMaker), hybrid cloud strategies, AI infrastructure for model serving and distributed training, expertise in LLMs/SLMs (including fine-tuning and deployment), hands-on experience with Hugging Face, and familiarity with agentic frameworks (e.g., LangChain, AutoGen) and Model Context Protocol (MCP) will significantly strengthen your candidacy and open up advanced project opportunities.
• Strategic Mindset: This role requires the ability to contribute to or set strategy, drive requirements, and influence technical direction.
• Risk and Control Awareness: A demonstrated understanding of risk management and controls within a financial services context is important.

Barclays is committed to fostering a culture of Respect, Integrity, Service, Excellence, and Stewardship, alongside a proactive "Empower, Challenge, Drive" mindset. This role provides an excellent platform for ambitious engineers to grow their careers, make a significant impact, and contribute to the future of AI in financial services.