Lead Platform Engineer

Salary / Rate: $220,000 – $300,000 (base salary only; excludes additional compensation or benefits)

About the role

To design, develop, and improve software that provides business, platform, and technology capabilities for Barclays’ customers and colleagues. This role involves leading the global Front-Office (FO) engineering success function, building trusted relationships with Quants and Strats worldwide, and influencing the platform roadmap to meet FO user needs.

Responsibilities

• Build and lead the global FO engineering success function across New York, London, and APAC users.
• Establish trusted relationships with Quants and Strats globally, understanding desk-specific needs and priorities.
• Prioritize and manage work intake based on business impact and urgency.
• Serve as the voice of FO users to influence platform roadmap and feature prioritization.
• Write high-quality Python code for automation, integrations, internal utilities, and FO tooling.
• Diagnose complex issues across cloud (AWS), distributed systems, Python stacks, notebooks, model pipelines, and APIs.
• Deliver engineering solutions that reduce recurring FO friction and accelerate delivery.
• Guide global front-office teams on secure and scalable usage of AWS services (S3, IAM, Lambda, ECS/EKS, Step Functions, CloudWatch, Glue, CDK/CloudFormation).
• Provide hands-on help with debugging, deployment, permissions, networking, and performance in AWS environments.
• Enable global FO teams to onboard onto platform AI features such as inference gateways, embeddings, evaluation tools, and tracing.
• Provide guidance on AI/ML concepts: model inference, RAG, embeddings, vector stores, latency optimization, and guardrails.
• Support adoption of tools such as LiteLLM, MLflow, Langfuse, Mem0, Databricks, SageMaker, and Observe.
• Establish global support processes, workflows, and standards for FO engineering.
• Identify patterns in recurring issues and partner with platform engineering to eliminate them via features or automation.
• Develop and maintain documentation, onboarding guides, and best practices tailored for FO developers.
• Drive proactive monitoring of systems impacting FO teams.
• Lead and mentor a small team of engineers focused on FO success, setting strong engineering standards for code quality, reliability, and responsiveness.
• Promote a culture of collaboration, empathy, accountability, and excellence.
• Ensure all FO support and deployment workflows comply with governance, model controls, and data privacy requirements.
• Promote secure-by-default patterns across global FO usage and enforce model governance standards and audit requirements.
• Development and delivery of high-quality, scalable, and maintainable software solutions.
• Collaborate cross-functionally with product managers, designers, and engineers to define requirements and ensure alignment with business objectives.
• Participate in code reviews and promote a culture of code quality and knowledge sharing.
• Stay informed of industry technology trends and contribute to Barclays’ technology communities.
• Adhere to secure coding practices to mitigate vulnerabilities and protect sensitive data.
• Implement effective unit testing practices to ensure code reliability.

Director Expectations

• Provide expert advice to senior functional management and committees to influence decisions outside of the function.
• Manage, coordinate, and enable resourcing, budgeting, and policy creation for a significant sub-function.
• Escalate breaches of policies or procedures appropriately.
• Foster and guide compliance, ensuring regulations are observed and processes are in place for adherence.
• Focus on the external environment, regulators, or advocacy groups to monitor and influence on behalf of Barclays.
• Demonstrate extensive knowledge of how the function integrates with the business division to achieve overall objectives.
• Maintain broad and comprehensive knowledge of industry theories, practices, and external market developments.
• Use interpretative thinking and advanced analytical skills to solve complex or sensitive problems.
• Exercise management authority to make significant decisions or strategic recommendations.
• Negotiate with and influence stakeholders at a senior level, both internally and externally.
• Act as the principal contact point for key clients and counterparts in other functions or business divisions.
• Serve as a spokesperson for the function and business division.

Leadership Behaviours

• L – Listen and be authentic: Demonstrate active listening and authenticity in leadership.
• E – Energise and inspire: Motivate and inspire teams to achieve excellence.
• A – Align across the enterprise: Ensure alignment with broader enterprise goals and initiatives.
• D – Develop others: Focus on developing and mentoring colleagues to help them thrive.

Values

• Respect: Treat colleagues, clients, and stakeholders with respect.
• Integrity: Uphold the highest standards of integrity in all actions.
• Service: Deliver exceptional service to clients and colleagues.
• Excellence: Strive for excellence in all aspects of work.
• Stewardship: Act responsibly as stewards of Barclays’ resources and reputation.

Mindset

• Empower: Empower teams to take ownership and drive results.
• Challenge: Encourage innovation and challenge the status quo.
• Drive: Demonstrate drive and commitment to achieving goals.

Requirements

• Strong Python engineering experience (backend, tooling, automation, debugging).
• Hands-on expertise with AWS: IAM, S3, Lambda, ECS/EKS, Step Functions, CloudWatch.
• Proven experience working with Quants, Strats, or front-office engineering teams.
• Solid understanding of AI/ML concepts (inference, vector search, embeddings, RAG, evaluation).
• Strong debugging abilities across cloud infrastructure, Python environments, containers, and pipelines.
• Excellent communication and stakeholder management skills in high-pressure FO environments.
• Experience leading a technical team or owning a global-facing engineering function.

Desirable Skills

• Familiarity with tools such as LiteLLM, MLflow, Databricks, SageMaker, Langfuse, Observe, Mem0.
• Understanding of financial markets, derivatives, FO analytics workflows, or pricing/risk models.
• Exposure to model governance, compliance, and data control frameworks.
• Experience with Docker, ECS/EKS, and platform observability tooling.
• Experience improving developer productivity or reliability at scale.