What you will be doing:
We are looking for driven, talented Software Engineers to help us build our SaaS-based anti-money laundering solutions, which help organisations 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-editions 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 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
- Trigger pipelines from and surface results as event streams over Kafka that scale efficiently and independently while minimising latency
- Write new features that enable our platform to understand articles in media, extract information about entities, apply ML models to categorise 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 prioritisation 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 have adopted a Kaizen culture to continually improve how we deliver and ensure we ship the best possible code and solutions to our customers.
About you:
As Software Engineer, you will have
- 4+ years of experience
- Experience writing production grade Python applications
- Experience writing tests and understand the importance of testing
- Experience with data pipelines
- Experience working in an agile environment and pair programming
- Experience working on the cloud (AWS/Azure/GCP) and/or using containerised infrastructure (Kubernetes/Docker) although the infrastructure itself will be provided by an SRE team
Nice to have:
- Experience working in a multi-disciplinary team of Data Scientists, ML Engineers, SREs and product managers
- Experience working with knowledge graphs or graph databases
- Experience with relevant machine learning techniques and graph algorithms
Education:
- BSc/BA degree in computer science, engineering or related discipline OR relevant years of experience in required skills.
What’s in it for you?
- Equity as we want you to have a part of what we are building
- 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.
