Senior Software Engineer (AI & SaaS Applications)

Join our team as a Senior Software Engineer, where you'll work on industry-leading technology and make a meaningful impact on our core SaaS products. You'll design and implement new features, collaborate with the Product Owner, contribute to AWS infrastructure, mentor junior engineers, and uphold quality excellence. Enjoy a competitive salary, 25 days of holiday, private medical insurance, and a combination of remote and London-based office working.

• Contribuer à la conception, à la mise en œuvre et à l'évolution de microservices évolutifs, fiables et sécurisés pour les produits SaaS.
• Adopter et promouvoir les outils d'ingénierie AI, les assistants de codage pilotés par LLM et les workflows automatisés pour améliorer la vitesse de livraison et la qualité du code.
• Travailler en étroite collaboration avec le Product Owner pour comprendre les exigences complexes en matière de données financières et les traduire en tâches d'ingénierie bien définies.
• Collaboration & Communication: Strong communication skills with the ability to work effectively across engineering and product stakeholders, asking the right questions and keeping work aligned to outcomes
• Navigating Ambiguity: Comfortable working in fast-moving, ambiguous environments, with a tendency to reduce complexity and work towards clear, practical decisions
• Leadership: Proven experience designing and delivering solutions in a fast-paced agile environment. Able to take ownership of engineering tasks end-to-end, drive progress without close supervision, and influence technical decisions constructively within a team
• Modern Tooling & AI Literacy: Hands-on experience using AI engineering tools (e.g. Claude, GitHub Copilot, Cursor, LLM APIs, or automated agent workflows) to improve day-to-day productivity
• SaaS Architecture: Solid experience developing single-tenant and multi-tenant B2B SaaS applications using Python REST APIs and distributed microservices, including exposure to Enterprise SaaS delivery
• FinTech / Capital Markets: Exposure to high-performance SaaS applications in front-office capital markets or data-intensive financial environments
• AWS & Infrastructure: Practical experience with core AWS services (Cognito, Lambda, Fargate, API Gateway, S3, IAM) and Infrastructure as Code via Terraform. Familiarity with IAM least-privilege patterns and CloudWatch Logs for observability
• PostgreSQL & Data Layer: Good working knowledge of PostgreSQL for relational data modelling, query optimization, and interacting with production database environments
• Mentorship: A genuine interest in supporting colleagues' growth — comfortable giving constructive feedback in code reviews, explaining technical decisions clearly, and helping less experienced engineers develop good habits and confidence, without needing a formal leadership title to do so
• Big Data & Analytics: Familiarity with high-scale data tools such as DuckDB, pandas, Spark, Databricks, or Snowflake
• Data Skills: Experience in data science and financial data visualization applications, particularly using TypeScript to build complex data interfaces
• Broader AWS Skill Set: Experience with additional AWS services such as SQS, SNS, Step Functions, EventBridge, or Secrets Manager to support event-driven, resilient architectures
• AI/ML Workflows: Some exposure to semantic search, vector databases, or LLM orchestration frameworks (e.g., LangChain, LlamaIndex)
• Agile Delivery: Understanding of continuous delivery practices and experience optimizing local-to-cloud development environments
• Front-End Data Skills: Proficiency in TypeScript for building data science interfaces and financial data visualisations