Senior Software Engineer - Backend & Distributed Systems Engineer

Build Production Backend Systems: Design, build and maintain reliable Python services, APIs and data-intensive applications operating at scale.

Develop Event-Driven Architecture: Help move our architecture from scheduled pipelines towards real-time services using messaging, queues, asynchronous processing and distributed workflows.

Build Systems for AI Agents: Develop the production software required to run increasingly agent-driven AI workflows, including state management, task execution, model routing, retries and observability.

Scale our Cloud Platform: Build and evolve highly available production systems across AWS, Kubernetes/EKS, ECS, Docker, RDS/PostgreSQL and S3.

Productionise AI Workloads: Work closely with our AI engineers to deploy and operate NLP, LLM and quantitative-model workloads, including workloads using our in-house GPU infrastructure.

Own Software Through to Production: Take responsibility for testing, deployment, performance, monitoring and reliability rather than handing code over to a separate operations team.

Automate Delivery and Infrastructure: Manage infrastructure using Pulumi or Terraform and improve automated testing and deployment through GitHub Actions.

Improve Reliability and Observability: Build effective monitoring, logging, tracing and alerting across our data, service, model and agent infrastructure.

7+ years of professional experience in software engineering, backend engineering, distributed systems, platform engineering or a closely related role.

Strong Python experience , including building and maintaining production software, services or APIs.

Deep AWS experience , ideally including EKS or ECS, RDS/PostgreSQL, S3 and Lambda.

Distributed Systems Experience: A strong understanding of event-driven architectures, messaging, asynchronous processing and distributed workflows.

Strong Engineering Fundamentals: A good understanding of software architecture, Linux, networking, databases and cloud infrastructure.

Production Ownership: Experience taking systems from design and implementation through to deployment, monitoring and ongoing operation.

Infrastructure-as-Code: Experience with Pulumi, Terraform or an equivalent framework.

CI/CD and Automated Testing: Experience with GitHub Actions or similar tooling, automated testing and reliable deployment processes.

Startup Mindset: Proactive, resourceful and comfortable taking responsibility in a small, fast-moving engineering team.

Experience with Apache Airflow, Kubernetes, real-time data platforms, AI/ML infrastructure, LLM agents, GPU infrastructure or financial-market systems would be useful, but is not essential.

Real Ownership: Take responsibility for important production systems and influence how they develop.

Technically Demanding Work: Build across backend software, distributed computing, cloud infrastructure and production AI.

Direct Influence: Work closely with our founder and have a meaningful voice in architecture and technology decisions.

Real Production Impact: Your work will quickly reach production and support leading financial institutions.

Build the Next Generation: Help shape our move towards a real-time, event-driven and agent-driven architecture.

Hybrid Flexibility: Spend at least three days a week in our Vauxhall hub.