Lead Platform Engineer

**Job Description** =================== **Purpose of the role** To design, develop and improve software, utilising various engineering methodologies, that provides business, platform, and technology capabilities for our customers and colleagues.  **Accountabilities** * Development and delivery of high-quality software solutions by using industry aligned programming languages, frameworks, and tools. Ensuring that code is scalable, maintainable, and optimized for performance. * Cross-functional collaboration with product managers, designers, and other engineers to define software requirements, devise solution strategies, and ensure seamless integration and alignment with business objectives. * Collaboration with peers, participate in code reviews, and promote a culture of code quality and knowledge sharing. * Stay informed of industry technology trends and innovations and actively contribute to the organization’s technology communities to foster a culture of technical excellence and growth. * Adherence to secure coding practices to mitigate vulnerabilities, protect sensitive data, and ensure secure software solutions. * Implementation of effective unit testing practices to ensure proper code design, readability, and reliability. **Director Expectations** * Provide expert advice to senior functional management and committees to influence decisions made outside of own function, offering significant input to function wide strategic initiatives. * Manage, coordinate and enable resourcing, budgeting and policy creation for a significant sub-function. * Escalates breaches of policies / procedure appropriately. * Foster and guide compliance, ensure regulations are observed that relevant processes in place to facilitate adherence. * Focus on the external environment, regulators, or advocacy groups to both monitor and influence on behalf of Barclays, when appropriate. * Demonstrate extensive knowledge of how the function integrates with the business division / Group to achieve the overall business objectives. * Maintain broad and comprehensive knowledge of industry theories and practices within own discipline alongside up-to-date relevant sector / functional knowledge, and insight into external market developments / initiatives. * Use interpretative thinking and advanced analytical skills to solve problems and design solutions in often complex/ sensitive situations. * Exercise management authority to make significant decisions and certain strategic decisions or recommendations within own area. * Negotiate with and influence stakeholders at a senior level both internally and externally. * Act as principal contact point for key clients and counterparts in other functions/ businesses divisions. * Mandated as a spokesperson for the function and business division. All Senior Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others. All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave. **Key Responsibilities** * **MLOps Leadership**: Build and evolve model deployment pipelines, registries, and monitoring frameworks. * **Tooling & Integration**: Implement and optimize **SageMaker**, **Databricks**, **MLflow**, and related orchestration tools. * **Governance & Risk**: Ensure compliance with **model governance**, **auditability**, and **AI safety standards**. * **Operational Excellence**: Drive reproducibility, lineage tracking, drift detection, and rollback strategies. * **Hands-On Delivery**: Write production-grade Python code for automation, orchestration, and monitoring. * **Collaboration**: Partner with data scientists, quants, and infra teams to align MLOps capabilities with business needs. * **Mentorship**: Coach engineers on best practices for ML lifecycle management and secure deployment. **Required Skills** * Strong Python engineering background. * Deep experience with **SageMaker**, **Databricks**, **MLflow**, and CI/CD for ML. * Proven track record in **operationalizing ML models at scale**. * Knowledge of **model governance**, compliance, and risk management. * Familiarity with **feature stores**, **model registries**, and **observability tools** (Langfuse, Observe). **Preferred Tech** * Kubernetes (EKS/on-prem), Airflow, Step Functions for orchestration. * Databricks for data engineering and ML pipelines. * MLflow for experiment tracking and model registry. * SageMaker for training and deployment. * Langfuse for evaluation and tracing.