Senior Backend Engineer

causaLens is the pioneer of Causal AI — a giant leap in machine intelligence.

We are on a mission to build truly intelligent machines, machines that truly understand cause and effect— it’s hard but super fun! If you want to build the future and are looking for a place that values your curiosity and ambition, then causaLens is the right place for you. Everything we do is at the forefront of technological advancements, and we are always on the lookout for people to join us whose skills and passion tower above the rest.

Since the company was established in 2017, causaLens has:
🥳Launched decisionOS, the first and only enterprise decision making platform powered by Causal AI - here

🚀Open sourced two of our internal tools and packages to support the open-source community, see Dara and Causal Graphs.

🦄Raised $45 million in Series A funding
🏆Been named a leading provider of Causal AI solutions by Gartner - here
🚀Included in Otta’s 2022 Rocket List as one of the fastest-growing companies to launch your career

At causaLens we are building the world's most advanced Causal AI powered decision intelligence platform for Data Scientists. The platform leverages state of the art Causal AI algorithms and models to empower data scientists and decision-makers to go beyond correlation-based predictions and have a real impact on the most important decisions for the business. Our platform is trusted and used by data science teams in leading organizations and provides real value across a wide variety of industries, and it's only the beginning.

Our Mission

To radically advance human decision-making.

A world in which humans leverage trustworthy AI to solve the greatest challenges in the economy, society and healthcare.
Head to our website homepage and watch the ‘Why Causal AI’ video to learn more.

The Role

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.

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)