Software Engineer (AI & SaaS Applications

As a Senior Software Engineer, you will design and implement new features within a collaborative team of Python & TypeScript engineers, working closely with the SaaS Product Owner. You will embrace modern AI agent tools and automated workflows to accelerate your own delivery, contribute to a culture of quality and good engineering practice, and support the growth of colleagues around you, * Design & Build: Contribute to the design, implementation, and evolution of scalable, reliable, and secure microservices for our core SaaS products, including Enterprise SaaS solutions across single- and multi-tenant architectures.

• AI Tooling & Productivity: Adopt and champion AI engineering tools, LLM-driven coding assistants, and automated workflows to improve your own delivery speed and code quality.
• Product Collaboration: Work closely with the Product Owner to understand complex financial data requirements and translate them into well-scoped engineering tasks. Bring a product-aware mindset and comfort navigating ambiguity to deliver clear, considered solutions.
• Cloud Operations & Observability: Contribute to AWS infrastructure including leveraging CloudWatch Logs for monitoring, diagnostics, and incident support, maintaining operational excellence across services.
• Mentorship & Peer Growth: Actively support the development of junior and mid-level engineers through thoughtful code reviews, sharing technical context, and being a reliable point of guidance. Contribute to raising the bar of engineering practice across the team without taking on a formal line management or lead responsibility.
• Quality Excellence: Write well-tested, maintainable code and contribute to CI/CD pipelines and quality standards across the team

• 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.
• 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.
• 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.
• 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.
• 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.
• Navigating Ambiguity: Comfortable working in fast-moving, ambiguous environments, with a tendency to reduce complexity and work towards clear, practical decisions.
• 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.

Desirable Skills

• Data Skills: Experience in data science and financial data visualization applications, particularly using TypeScript to build complex data interfaces.
• FinTech / Capital Markets: Exposure to high-performance SaaS applications in front-office capital markets or data-intensive financial environments.
• 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.
• Big Data & Analytics: Familiarity with high-scale data tools such as DuckDB, pandas, Spark, Databricks, or Snowflake.
• 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

• Competitive salary
• 25 days holiday plus bank holidays
• Discretionary Bonus
• Pension Scheme
• Private Medical Insurance
• Work remotely abroad for up to 40 business days each year
• Life Insurance
• Childcare Nursery Scheme
• Combination of remote and London-based office working, with 2 days in the office per week.
• A yearly Well-being Physical Activity budget
• Continuous learning through funded training and challenging projects
• Collaborative culture
• Weekly team lunches
• Free Fruit, snacks, and drinks provided throughout the day (When office-based)
• Regular Team Socials
• Cycle to Work Scheme

BMLL is the leading independent provider of harmonised Level 3, 2 and 1 historical data and analytics across global equities, ETFs, futures and US equity options. We provide market participants with immediate access to granular T+1 order book data and advanced analytics, enabling them to accelerate research, optimise trading strategies, and better understand market behavior.

BMLL was acquired in 2025 by Nordic Capital, alongside minority shareholder Optiver, marking a joint commitment to accelerate the company’s next phase of growth. We offer an inclusive and collaborative culture, a hybrid working environment that includes regular days in our London office, weekly team lunches, and a variety of out-of-hours social activities.

For more information, visit our website or follow us on X (@bmlltech) and LinkedIn @ bmll, This is an exciting opportunity to work on industry-leading technology and make a meaningful impact on our core SaaS products. The BMLL Lab & Vantage products are the market-leading applications for data science and data visualisation on the largest financial datasets.