Cognite operates at the forefront of industrial digitalization, building AI and data solutions that solve some of the world’s hardest, highest-impact problems. With unmatched industrial heritage and a comprehensive suite of AI capabilities, including low-code AI agents, Cognite accelerates the digital transformation to drive operational improvements.

Our moonshot is bold: unlock $100B in customer value by 2035 and redefine how global industry works.

What Cognite is Relentless to achieve

We thrive in challenges. We challenge assumptions. We execute with speed and ownership. If you view obstacles as signals to step forward - not step back - you’ll feel at home here. Join us in this venture where AI and data meet ingenuity, and together, we forge the path to a smarter, more connected industrial future.

How you’ll demonstrate Ownership

We are seeking a customer-focused Software Engineering Manager at Cognite’s HQ in Phoenix, AZ to lead a team of 5-10 engineers, developing services and applications for industrial AI. Atlas AI is Cognite’s agent builder workbench and agentic runtime that uses LLMs, RAG, and other tools to help optimize and automate industrial business processes leveraging a contextualized knowledge graph. In this role, you will be responsible for leading a high-performing team to drive the development of technologies that transform industrial operations and make data interaction intuitive, effortless, and empowering. Your work will directly impact industrial efficiency and sustainability, which is critical to our mission of powering a high-tech, sustainable, and profitable industrial future.

The ideal candidate will have a proven track record of leading technology teams, a deep understanding of SaaS software, and a passion for driving innovation. As a technical leader, you will collaborate with a cross-functional team consisting of designers, product managers, and program managers to ensure the team builds the right product that is of excellent quality and is delivered on time.

The Impact you bring to Cognite

• Lead a team of 5-10 software engineers.
• Develop services, applications, and AI agents and tools to enable industrial software customers to unlock the value of their operational data, and automate complex workflows.
• Drive the team to build, operate, and support production-grade SaaS software, including establishing on-call rotations, defining service level objectives (SLOs), and ensuring a fast and effective incident response process.
• Champion a culture of quality by establishing automated code coverage goals, implementing comprehensive telemetry and monitoring for all services, and developing robust testing strategies to ensure the reliability and scalability of our industrial AI solutions.
• Coach engineers to have a high impact on the team, regardless of their background, seniority, or understanding of the domain.
• Collaborate with a cross-functional team consisting of designers, product managers and program managers to ensure the team builds the right product, that is of excellent quality and is delivered on time.
• Collaborate with industrial domain experts to deeply understand pain points, unmet needs, and opportunities to enhance operational efficiency through AI and data liberation.
• Unblock the team and collaborate with stakeholders outside the team to resolve and mitigate problems.
• Help your team with code reviews and documentation, and write code yourself.

Required Qualifications

• Bachelor's or Master’s degree in Computer Science or related field, or equivalent practical experience.
• 10+ years of software engineering experience.
• 5+ years of experience leading and managing software engineers.
• Expertise relevant to our tech stack. Kubernetes systems in a multi-cloud environment (Azure, AWS, GCP), frontend TypeScript and React, backend Python.
• Understanding of software engineering and best practices for the full development life cycle including coding standards, build processes, testing, and operations.
• Understanding of generative AI and/or machine learning, and familiarity with the tools and methodologies around them, for instance for measuring accuracy.

Preferred Experience

• Experience building applications on top of AI/ML models or large language models (LLMs).
• Strong verbal and written communication skills.
• A genuine and keen interest in building the competency of engineers.