Cognite

Industrial data platform with AI

Software Engineering Manager - Atlas AI

Engineering LeadershipPosted on Nov 10

Full-timePhoenix, AZ, USANo salary listed

About the Job

Requirements

A Bachelor's or Master's degree in Computer Science or a related field, or equivalent practical experience.
At least 10 years of software engineering experience.
At least 5 years of direct people management experience, with a track record of building, scaling, and retaining strong engineering teams.
Deep technical expertise in modern cloud architectures, scalable microservices, Python backends, TypeScript and React frontends, and Kubernetes deployed across Azure, AWS, and GCP multi-cloud environments.
Understanding of software engineering best practices across the full development life cycle, including coding standards, build processes, testing, and operations.
Understanding of generative artificial intelligence and/or machine learning, and familiarity with related tools and methodologies, such as measuring accuracy.
Experience building applications on top of artificial intelligence or machine learning models, or large language models.
Strong verbal and written communication skills.
A genuine interest in building engineers’ competency.

Responsibilities

Lead, inspire, and mentor a team of 5–10 software engineers, fostering career growth and technical excellence.
Develop services, applications, artificial intelligence agents, and tools to help industrial software customers unlock operational data and automate complex workflows.
Drive the team to build, operate, and support production-grade software as a service, including establishing on-call rotations, defining service level objectives, and ensuring a fast and effective incident response process.
Establish automated code coverage goals, implement comprehensive telemetry and monitoring for all services, and develop testing strategies to ensure the reliability and scalability of industrial artificial intelligence solutions.
Coach engineers to have a high impact on the team regardless of their background, seniority, or domain understanding.
Collaborate with designers, product managers, and program managers to ensure the team builds the right product to excellent quality and delivers it on time.
Collaborate with industrial domain experts to understand pain points, unmet needs, and opportunities to enhance operational efficiency through artificial intelligence and data liberation.
Unblock the team and collaborate with stakeholders outside the team to resolve and mitigate problems.
Provide architectural guidance and system design oversight, conduct code reviews, and contribute to core codebases when needed.

What Cognite is Relentless to Achieve

Cognite operates at the forefront of industrial digitalization, building AI and data solutions that solve the world’s hardest, highest-impact problems. Our Moonshot is bold: unlock $100B in customer value by 2035, and redefine how global industry works.

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.

Responsibilities

Lead, inspire, and mentor a high-performing team of 5-10 software engineers, fostering career growth and technical excellence.
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.
Provide architectural guidance and system design oversight, conduct code reviews, and remain hands-on by contributing to core codebases when needed.

The Impact you bring to Cognite

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 direct people management experience with a track record of building, scaling, and retaining strong engineering teams.
Deep technical expertise in modern cloud architectures, scalable microservices, and our core stack: Python backends, TypeScript/React frontends, and Kubernetes deployed across multi-cloud environments (Azure, AWS, GCP).
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.
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.

A snapshot of our many perks and benefits as a Cogniter

Competitive compensation
401(k) with employer matching
Competitive health, dental, vision & disability coverages for employees and all dependents
Unlimited PTO
Paid Parental Leave Program
Employee Referral Program

Why Cognite

You will work at the forefront of Industrial AI, partnering with some of the world's leading industrial organisations to solve problems that actually matter at scale — not hypothetical ones. You'll join a collaborative, fast-moving environment where curiosity and ownership are the norm, not the exception. If you want delivery work you can point to and be proud of, we'd love to hear from you.

Equal Opportunity

Cognite is committed to creating a diverse and inclusive environment at work and is proud to be an equal opportunity employer. All qualified applicants will receive the same level of consideration for employment.

About the Company

Cognite

Industrial data platform with AI

Cognite provides cloud-based data and AI platforms for industrial companies to digitize and optimize operations. Its flagship Cognite Data Fusion connects OT, IT, and engineering data, unifying sensor data, maintenance logs, and 3D models into a real-time view of assets to improve performance and safety. Cognite Atlas AI is a low-code platform that lets engineers build AI agents for predictive maintenance, anomaly detection, and production optimization without deep coding. The company differentiates itself through deep cross-domain data integration for asset-heavy industries and a scalable cloud environment to accelerate industrial digitalization and deliver measurable value.

Company size: 501-1,000
Company stage: Acquired
Total funding: $225.3M
Headquarters: Tempe, AZ
Founded: 2016

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