Job Description

Hybrid requirements: This role has flexible working patterns.
We are looking for exceptional and ambitious individuals to develop our Causal AI platform. We are looking for motivated and high-achieving Senior Backend Software Engineers, based in London, to join our Engineering team. This is a full-time placement with significant opportunities for non-linear growth.
Your focus will be on designing, implementing and maintaining our multi-tenanted, multi-cloud data science platform. You'll be responsible for service and API design, backend python implementation, CI/CD rollout and meeting quality standards. Your remit will include multiple aspects of our multi-service platform, from AuthN to Data Integration and flow orchestration.
The broader application stack includes Python, FastAPI, Postgres, Github, Kubernetes, Helm, Terraform, AWS, GCP, Azure and other technologies.

A day in the life of the role:

Collaborate closely with product managers, team leads and other senior engineers to understand the needs and requirements of services.
Design and implement APIs, services and packages to help meet user's needs.
Develop and enhance CI/CD flows, improving quality, accountability and standards across the product stack.
Work directly on integrating key elements of MLOps workflow with causal AI capabilities, ensuring robustness, scalability, and efficiency.
Collaborate with cross-functional teams including data science, software engineering, and product to align technical solutions with business objectives and user needs.

Job requirements

This role offers a unique opportunity to leverage expertise in both Cloud Native Infrastructure and Python engineering to ensure the users spend their time building value and not setting up systems. If you are passionate about building smooth running systems that break down and simplify complex flows, we encourage you to apply and contribute to our team.

You have:

Bachelor's or Master's degree in Computer Science, Physics, Maths, or a related field or equivalent industry experience.
3-5 years of professional experience in a production python cloud application, machine learning engineering, or a related role, with exposure to deploying machine learning models into production.
Demonstrably strong Python skills with experience in distributed systems
Strong knowledge and experience with Cloud Native Infrastructure (GCP, Azure, AWS) with demonstrable skills in using and managing Kubernetes clusters
Good knowledge of DevOps tools and technologies, such as Helm, Docker, Terraform and CI/CD pipelines (GitHub Actions)
Knowledge of MLOps especially on cloud environments: Vertex, Sagemaker, Synapse, is a huge plus.
Strong Knowledge of the software development lifecycle (code review, version control, tooling, testing, etc.)
Understanding of the full stack would be ideal (REST backends and SPA frontends)
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Role tech stack
Python


Microsoft Azure


AWS


Google Cloud Platform


Kubernetes


Helm