Staff Software Engineer
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Requirements
• A passion for the craft, you're driven by engineering excellence and committed to fostering that culture across the team. • A passion for the craft, • Strong software engineering foundations, solid grasp of algorithms, data structures, and system design. You write clean, maintainable, testable code and have strong command of Golang or Rust and Python. • Strong software engineering foundations, • Distributed systems and data engineering experience, proven track record building big data processing platforms in production, moving beyond scripting to robust engineering solutions (e.g., Databricks/Delta Lake, Snowflake, BigQuery). Hands-on experience architecting Data Warehouses and Data Lakes. • Distributed systems and data engineering experience, • API and service design maturity, experience designing multi-service systems with attention to schema governance, forward compatibility, and data access patterns. • API and service design maturity, • Multimodal data handling, experience working with storage engines or databases that handle diverse data types, including relational data, vector embeddings, and large binary blobs. • Multimodal data handling, • Security awareness, familiarity with designing for security requirements and participating in security testing and compliance workflows. • Security awareness, • Reliability and observability mindset, experience providing QoS guarantees, implementing monitoring and alerting, and optimising observability in production. • Reliability and observability mindset, • CI/CD and deployment expertise, hands-on experience building and optimising CI/CD pipelines, including multi-service and zero-downtime deployments across numerous customer environments. • CI/CD and deployment expertise, • Diagnostic and optimisation skills, proactive approach to diagnosing performance bottlenecks in data processing and storage systems. • Communication and leadership, excellent communication skills to understand data needs from research scientists and translate them into technical specifications. Experience mentoring engineers and facilitating technical decisions. • Communication and leadership, • Incremental mindset, you work in small steps toward larger goals, driving change through continuous improvement rather than massive redesigns. You can zoom in on details and zoom out to see the big picture. • Incremental mindset, • Ideally • Polyglot programming, deep expertise in Python and mastery of high-performance compiled languages like Golang, C++, or Rust. • Polyglot programming, • Big data scale, experience designing and maintaining big data systems, with a track record of running complex analytics on massive datasets in production. • Big data scale, • Advanced testing, experience with fuzzing, deterministic simulation testing, or fault injection in production systems. • Advanced testing, • Kubernetes expertise, ability to leverage resources that extend the Kubernetes API (e.g., CRDs, Operators) and infrastructure configuration tools (Crossplane, ArgoCD, Helm charts). • Kubernetes expertise, • Infrastructure flexibility, understanding of what it takes to build software that runs in cloud, on-premises, and air-gapped environments. • Infrastructure flexibility,
Responsibilities
• Design and architect scalable distributed systems, microservices, and APIs for high-dimensional simulation data across deep learning surrogate data generation and ML lifecycle. • Build and maintain user-centric systems that are both reliable and performant. • Architect and integrate modern Data Warehouses, Data Lakes, and high-performance storage solutions to handle the unique demands of complex simulations, multimodal data and deep learning workloads. • Define system architecture for new capabilities, making trade-offs across performance, reliability, cost, and developer experience. • Own your work end-to-end: from architectural design through deployment and maintenance in a fast-paced, agile environment. • Authentication and permissions: understanding of implementing and managing authentication mechanisms, authorization models, and fine-grained access control systems in distributed environments. • Define reliability guarantees, quality of service metrics, and performance standards for the services you own. Proactively diagnose and resolve complex performance bottlenecks. • Develop and enforce API schema standards and schema drift mitigation strategies. Ensure compliance with established patterns for security, data segregation, and access control. • Drive best practices in CI/CD, automated testing, observability, and infrastructure-as-code. Build and maintain deployment pipelines, including zero-downtime and multi-service deployments. • Author and review Technical Decision Records. Participate in Technology Radar reviews to evaluate and adopt new tools and approaches. • Mentor junior and mid-level engineers, facilitate technical discussions, build consensus around architectural decisions, and translate research needs into well-defined technical requirements. • Influence engineering roadmap and contribute to technical strategy beyond your immediate team.
Benefits
• Equity options – share in our success and growth. • 10% employer pension contribution – invest in your future. • Free office lunches – great food to fuel your workdays. • Flexible working – balance your work and life in a way that works for you. • Hybrid setup – enjoy our new Shoreditch office while keeping remote flexibility. • Enhanced parental leave – support for life’s biggest milestones. • Private healthcare – comprehensive coverage • Personal development – access learning and training to help you grow. • Work from anywhere – extend your remote setup to enjoy the sun or reconnect with loved ones. • We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics. • We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.
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