Senior Backend Software Engineer, Atlas AI

About the role

Cognite is seeking a Senior Backend Software Engineer to join our team. This role is critical in scaling our AI capabilities, with a focus on building robust, scalable backend services that power intelligent agents and integrate them into Cognite's core offerings.

Responsibilities

• Build Scalable Systems: Design and implement resilient backend services and APIs that can handle high volumes of industrial data and complex AI workflows.
• Orchestrate Industrial AI: Evaluate, implement, and benchmark Large Language Models (LLMs) and AI agents, focusing on the backend infrastructure required to serve these models at scale.
• Drive Operational Excellence: Champion a "built to run" mindset by implementing comprehensive telemetry, automated testing, and CI/CD patterns to ensure our SaaS offerings meet strict Service Level Objectives (SLOs).
• Collaborate Cross-Functionally: Work closely with frontend engineers, product managers, and industrial domain experts to translate complex customer needs into elegant technical solutions.

Requirements

• 5+ years of professional software development experience, with a focus on backend systems.
• Python Expertise: Authoritative knowledge of Python and its ecosystem. Experience with other languages like Kotlin, Java, or Rust is a plus.
• Cloud Native Proficiency: Extensive experience designing and operating large-scale systems in a multi-cloud environment using Kubernetes, Docker, and Terraform.
• Distributed Systems: Proven track record of building scalable APIs and microservices that interact with complex data stores (SQL, NoSQL, or Graph databases).

Preferred Experience

• Applied AI Interest: A strong interest in (or experience with) LLMs and AI/ML frameworks. You are excited to build the "plumbing" that makes AI useful in a production industrial setting.
• Ownership Mentality: You don't just write code; you take responsibility for how that code performs in production and how it solves the customer's problem.
• Communication: Excellent verbal and written English communication skills; able to explain complex architectural trade-offs to both technical and non-technical stakeholders.
• Experience building production-grade applications on top of LLMs (OpenAI, Anthropic, LangChain, etc.).
• Knowledge of GraphQL or graph databases (e.g., Neo4j).
• Familiarity with industrial protocols (OPC-UA, MQTT) or time-series databases.
• Prior experience in a high-growth SaaS environment with a strong engineering culture.
• Experience with Infrastructure as Code (e.g., Terraform) and managing containerized workloads in Kubernetes.
• Familiarity with building and maintaining automated deployment pipelines using Jenkins, GitHub Actions, or similar tools.