Sr Lead Software Engineer CFS CEA UK

Description

Cloud Engineering Acceleration (Team XLR8) accelerates delivery by going where the need is greatest and solving high-impact problems to deliver public cloud solutions reliably and securely for the biggest bank in the world. We partner with platform teams and are trusted to tackle the hardest problems first—earned through consistent delivery and a strong commitment to quality—so our recommendations carry real weight.

We work across a variety of tech stacks and domains while staying consistent in our engineering standards. We practice iterative development, Pair Programming, Test Driven Development, and Specification by Example, and we actively build engineering culture wherever we engage. The team invests in every engineer through dedicated learning time and a collaborative environment where knowledge-sharing is expected in both directions.

Job Responsibilities

• Design and implement platform services and infrastructure across public cloud environments, with a focus on architecture, integration patterns, and system reliability.
• Own the full Software Development Lifecycle, including automating CI/CD pipelines and local development environments (not just operating within them).
• Write, review, debug, and maintain secure, high-quality production code; hold team output to a consistent standard, including AI-generated code.
• Lead design reviews and architecture discussions to improve technical quality and drive better solutions.
• Collaborate with partner teams to evaluate, adopt, and scale tooling and methodologies—including agentic AI development practices—that improve developer experience and platform quality.
• Drive operational excellence by identifying recurring issues and resolving them through automation rather than tolerance.
• Provide leadership and accountability for delivery outcomes, technical direction, and day-to-day execution.
• Coach and mentor engineers; raise the bar on code quality, testing discipline, and engineering standards.
• Communicate clearly with technical and non-technical audiences, articulating the business value behind technical decisions.
• Influence and improve engineering culture and practices across teams you support.

Required qualifications, capabilities, and skills

• Formal training or certification in software engineering, backed by strong hands-on delivery experience.
• Excellent coding ability with well-reasoned, clearly held views on quality and testing.
• Demonstrated ownership of SDLC, including CI/CD automation and local development tooling.
• Practical cloud-native experience building and operating services on AWS, Azure, or GCP.
• Solid understanding of application resiliency and security.
• Expertise in at least one programming language, with the ability and willingness to learn additional stacks (e.g., Java, Go, Python, Terraform, Kubernetes) as needed.
• Confidence using and critically evaluating agentic AI development tools; applies judgment on correctness, quality, security, and performance rather than accepting outputs at face value.
• Leadership experience with accountability for delivery, technical direction, and coaching/mentoring.
• Strong communication skills across technical and non-technical audiences, including active listening and empathetic leadership.
• Clear understanding of business value behind technical decisions and the habit of applying that lens throughout delivery.

Preferred qualifications, capabilities, and skills

• Strong hands-on experience in Java, Go, and/or Python.
• Experience with Specification Driven Development and/or Behavior Driven Development.
• Hands-on experience with agentic development methodologies and tooling.
• DevOps experience across the delivery pipeline.
• Background in financial services or another heavily regulated environment.
• AWS, Azure, or GCP professional certification (or equivalent experience).
• Track record of coaching engineers or shaping technical practices across multiple teams (beyond a single team).
• Experience contributing to developer platforms, shared engineering capabilities, or internal platform tooling.