About the Role Join a pioneering team that’s redefining how AI and cloud-native platforms power front-office trading. We’re hiring a hands-on engineering leader to shape the future of our Dart platform, a critical infrastructure that supports Quantitative and Strat developers in building next-generation trading solutions. This is not just another engineering role. You’ll work side-by-side with front-office traders and quants, creating bespoke GenAI tools that directly impact trading performance. If you’re passionate about building something unique, ahead of the curve, and never done before, this is your chance to make it happen. What You’ll Do You’ll lead and innovate across both cloud and on-prem environments, scaling platform capabilities and driving AI adoption: Architect and develop cutting-edge platform services for AI-driven trading. Potentially lead a small team of engineers, driving technical excellence while staying hands-on. Collaborate with internal infra/platform teams to align capabilities and avoid duplication. Design and implement secure, cost-aware, scalable systems using AWS services and Kubernetes. Mentor junior engineers and set best practices for AI/ML infrastructure. Influence across organisational boundaries and champion modern engineering trends. Stay ahead of the curve in Generative AI, ML infrastructure, and cloud-native tooling. Tech Stack Programming: Python (Java familiarity is a plus). AWS: S3, Kinesis, Glue, Lambda, Step Functions, SageMaker, and more. On-Prem: Managed Kubernetes Platform and Hadoop ecosystem. Why This Role is Different Direct Impact: Build AI tools that traders and quants use daily to optimize strategies. Creative Freedom: Open collaboration and the chance to bring your ideas to life. Visibility: Be a big player in a small, high-impact team with exposure across the organisation. What We’re Looking For 10 years of extensive experience in software/data engineering, ideally in platform or infra roles. Strong programming skills in Python; passion for code quality and testing. Demonstrable experience applying GenAI concepts to front-office/capital market environments. Deep experience with AWS services (S3, Glue, Kinesis, Lambda, ECS, IAM, KMS, API Gateway, Step Functions, MSK, CloudFormation). Passion for being hands-on while enabling and growing a small engineering team. Nice to Have Experience with on-prem Hadoop and Kubernetes. Familiarity with AWS cost management and optimisation tools. Knowledge of front-office developer workflows in financial services.