Senior Software Engineer

What you will be doing:

We are looking for driven, talented Senior Software Engineers to help us build our SaaS-based anti-money laundering solutions, which help organizations fight financial crime.

The data-driven nature of the role and the prominence of Python in the data and ML ecosystem means you will primarily work in Python but any experience of other languages would be helpful.

We are building cutting-edge solutions that help prevent money flowing to and from bad actors to create a safer world. Your work will allow our customers to find out who is associated with crimes, financial and political risks, what that association is, and when it occurred, and it will dynamically update their state as new information emerges across a huge range of sources.

As a Senior Software Engineer, you will:

• Be working alongside our ML engineers, data scientists, and other software engineers within the tribe
• Build data-centric pipelines and the system around our knowledge graph to build the next-generation AML solution
• Write new features that enable our platform to understand articles in media, extract information about entities, apply ML models to categorize their actions, and merge all this with existing data we hold
• Be responsible for the quality of your code. Write tests, and take ownership of the systems that ensure the quality of our code
• Learn quickly and be able to adopt the technologies we use to develop code and deploy it
• Contribute to planning and to the right technical decisions, work with Product on the prioritization and the scoping of the team’s work, and be able to demo the features you’ve worked on to stakeholders
• Adopt best practices (and be able to suggest improvements to them), to get code from initial requirements to deployed services in production

Our Tech Stack:

• Our technology stack is designed to run on public cloud architectures, notably AWS and GCP
• We use Python and Kotlin in the backend and TypeScript, ES6 and React in the frontend
• We make substantial use of relational database technologies, notably Postgres, large scale noSQL technologies such as Cassandra, as well as Spark and cloud based object stores for big data processing
• We also use an event-sourced model powered by Kafka for our communication bus and gRPC for our intra-service communication protocol
• Our data and AI teams use a wide range of machine learning libraries, large scale hybrid columnar data stores such as Databricks, Spark for stream and big data processing in combination with Kafka, as well as some graph databases
• We use modern observability solutions (such as Datadog or Grafana) and deploy our code using ArgoCD

We have a strong emphasis on engineering excellence and strive to ship the best possible code and the best possible solutions to our customers.

About you:

• Experience building scalable backend applications (preferably with Python).
• A track record of working in multi-disciplinary teams alongside Data Scientists, ML Engineers, and Product Managers.
• Hands-on experience with cloud platforms (AWS, Azure, or GCP) or with containerized infrastructure (e.g., Kubernetes, Docker, ArgoCD, Argo Workflows).
• Strong communication skills and a collaborative mindset, with the ability to contribute to system design discussions and mentor more junior engineers.

Nice to have:

• Experience working with PySpark or other distributed data processing frameworks.
• Background in building data-intensive applications or distributed systems using map-reduce style architectures.
• Experience maintaining and scaling machine learning-powered applications in production environments.
• Familiarity with event-driven or microservice architectures.

What’s in it for you? 

• Equity as we want you to have a part of what we are building 
• Private medical insurance designed to keep you ensuring peace of mind while you excel in your career
• Unlimited Time Off Policy- A work-life balance and focus on our well-being are critical to keeping us performing at our best 
• We embrace a hybrid approach that requires employees to be in the office for two days a week. We strongly believe that this approach fosters collaboration and enables the building of meaningful relationships
• You will also get a new starter budget to kit out your home office 
• Opportunity to work on innovative projects with smart-minded people keen to share their knowledge and continuously improve 
• Annual learning budget (prorated based on start date) to drive your performance and career development