Senior Software Engineer - AI, Big Data an in London

PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.

PhysicsX is building a platform that enables Data Scientists and Simulation Engineers to build, train, and deploy Deep Physics Models. The platform handles massive volumes of complex simulation data and enables high-fidelity multi-physics simulation through AI inference.

We're looking for a Senior Software Engineer with a strong background in building data platforms. You won't just be moving data from A to B - you'll be architecting and building the distributed systems, services, and APIs that form the backbone of our platform. You'll bridge the gap between complex physical simulations and modern data infrastructure, implementing storage solutions for AI/ML pipelines and creating the analytical layers that allow our engineers to visualise and understand their results. This role is for builders who love coding robust software as much as designing efficient data architectures.

• Design and architect scalable distributed systems, microservices, and APIs for high-dimensional simulation data across the machine learning lifecycle — from data processing and model training to inference services.
• Build tools that enable data scientists and engineers to create automated, robust pipelines for data ingestion and processing — powering active learning loops.
• 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.
• Build internal tools that enable BI dashboards and scientific data visualizations, making large datasets intuitive and accessible.
• 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.
• Define reliability guarantees, quality of service metrics, and performance standards for the services you own.
• Proactively diagnose and resolve complex performance bottlenecks.
• 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.
• 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.

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.

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., Hands-on experience architecting Data Warehouses and Data Lakes).

API and service design maturity — experience designing multi-service systems with attention to schema governance, forward compatibility, and data access patterns.

User code execution — experience building systems that run user code safely, robustly, and securely, with an understanding of sandboxing, isolation, and threat models.

Multimodal data handling — experience working with storage engines or databases that handle diverse data types, including relational data, vector embeddings, and large binary blobs.

Security awareness — familiarity with designing for security requirements and participating in security testing and compliance workflows.

Reliability and observability mindset — experience providing QoS guarantees, implementing monitoring and alerting, and optimising observability in production.

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.

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.

Polyglot programming — deep expertise in Python and mastery of high-performance compiled languages like Golang, C++, or Rust.

Big data scale — experience designing and maintaining big data systems, with a track record of running complex analytics on massive datasets in production.

Domain knowledge — understanding of 3D geometry processing (meshes, point clouds) and data structures used in physics-based simulations.

Advanced testing — experience with fuzzing, deterministic simulation testing, or fault injection in production systems.

Infrastructure flexibility — understanding of what it takes to build software that runs in cloud, on-premises, and air-gapped environments.

We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. 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.