How you’ll demonstrate Ownership

We are seeking an AI Platform Engineer to join the Cognite Atlas AI Product team in Phoenix, AZ, to engineer, build, and operate the production-grade, multi-cloud platform that enables our internal and partner teams to build, deploy, and manage industrial AI agents. You will be responsible for creating the core services, frameworks, and infrastructure for our "agent builder workbench" and agent runtime, focusing on scalability, reliability, cost-efficiency, and security. 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 Impact you bring to Cognite

• Design, build, and maintain the core Python SDKs and services for the Atlas AI platform. Create clean abstractions that empower Solution Engineers to easily define and test agents and workflows.
• Build the core agentic runtime, ensuring it is scalable, meets its SLOs, and can reliably manage the state, orchestration, and execution of industrial agents.
• Develop a robust, governed, and secure framework for AI agent tool-use. Engineer the platform components that allow solution engineers to safely add new tools (e.g., API calls, database queries) and that manage the secure execution, monitoring, and access control for those tools.
• Manage the LLM serving layer, including deploying and optimizing models for low-latency/high-throughput inference. Build and maintain model routing logic to select the most appropriate model (e.g., performance vs. cost) for a given task.
• Implement evaluation and observability for all AI services. Create standardized frameworks for systematically evaluating the performance, accuracy, cost, and safety of LLMs and agentic workflows. Drive the implementation of robust, automated testing strategies for LLM-based systems.
• Own the full development lifecycle for services in a production SaaS environment. This includes establishing automated code coverage goals, rigorous code reviews, defining SLOs, participating in on-call rotations, and ensuring a fast and effective incident response process.
• Work closely with the Lead Architect to translate the technical vision into implemented, production-grade services. Act as a key partner for the Solution Engineers (your internal customers) to understand their needs and abstract common patterns into reusable, robust platform components.
• Stay up to date on the latest developments in the field, and mentor junior developers.

Required Qualifications

• Bachelor's or Master’s degree in Computer Science or a related field, or equivalent practical experience.
• 8+ years of professional experience in backend software engineering, platform engineering, or MLOps, with a proven track record of architecting and operating complex systems at scale.
• 2+ years of hands-on experience building applications or platforms on top of AI/ML models or LLMs.
• Expert-level proficiency in Python and a strong background in software architecture, robust API design, and building maintainable, well-documented SDKs for other developers.
• Hands-on experience with Kubernetes (K8s) and building services on managed PaaS in a multi-cloud environment (AWS, Azure, GCP). Strong understanding of Infrastructure as Code (e.g., Terraform).
• Proven experience building and operating production-grade SaaS software. Understanding of the full development life cycle, including CI/CD, monitoring, telemetry, and on-call incident response.
• Practical experience with LLM orchestration frameworks (Bedrock, Vertex, Semantic Kernel, LangChain).
• Strong verbal and written communication skills, with the ability to articulate complex technical designs and decisions clearly.

Preferred Experience

• Hands-on experience deploying and managing LLMs in production using high-performance serving frameworks.
• Experience with MLOps/LLMOps tools for tracing, monitoring, and evaluating LLM applications (LangSmith, Arize, Phoenix, or equivalent).
• Experience with RAG Infrastructure, embedding generation pipelines, vector database integrations, and high-performance vector similarity search APIs.

A snapshot of our many perks and benefits as a Cogniter

 

 

 

Learn more about us

 

 

 

• Impact 2025
• Cognite's Industrial AI: Moonshot
• We’re globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi.

 

 

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.

BASE SALARY: $150,000 to $190,000 per year, paid semi-monthly

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

TOTAL COMPENSATION

Base salary is set according to market rates for the nearest major metro and varies based on Launch Potato’s Levels Framework. Your compensation package includes a base salary, profit-sharing bonus, and competitive benefits. Launch Potato is a performance-driven company, which means once you are hired, future increases will be based on company and personal performance, not annual cost of living adjustments.

BASE SALARY: $150,000 to $190,000 per year, paid semi-monthly

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

TOTAL COMPENSATION

Base salary is set according to market rates for the nearest major metro and varies based on Launch Potato’s Levels Framework. Your compensation package includes a base salary, profit-sharing bonus, and competitive benefits. Launch Potato is a performance-driven company, which means once you are hired, future increases will be based on company and personal performance, not annual cost of living adjustments.

About the Internship   

Our Spring internship provides a hands-on experience in the fast-paced and exciting semiconductor industry. Our interns will work alongside industry projects and gain valuable insights into our core engineering roles. This program is designed to grow and shape the industry leaders of tomorrow, offering a chance to learn, develop and build the skills needed for a successful career in the semiconductor field.      

What to expect  

This position is a paid internship that is expected to start January/February 2027 and continue through April/May 2027. The duration will be 12 weeks, full time and on-site. Our internship program is for students who are actively enrolled in a full-time academic program. Recent graduates seeking employment after graduation and not returning to school should apply for our Early Career opportunities.  

International Students: Please consult with your school's international office prior to your application on your ability to pursue this internship opportunity.  

About the Role

We are seeking an experienced, highly motivated Senior Full-Stack Engineer to join our growing team. The ideal candidate will be a strong collaborator with deep expertise in modern application development technologies and practices. The focus of this role is on building and maintaining robust, scalable, and high-performance applications across the full stack using TypeScript and some Python. Some experience with React and/or Angular would be helpful.

This role requires not only technical proficiency but also a forward-thinking perspective on the role of Artificial Intelligence (AI) in modern software development. Candidates must demonstrate an active engagement with AI tools, understanding their practical use, current limitations, and the strategic opportunities they present for the engineering discipline.

Mainly remote work: seeking candidates in the greater Los Angeles area to mainly work remotely with some on-site work required at times.

Key Responsibilities

• Lead the design, development, and deployment of complex features across both the frontend and backend of our clients’ products.
• Write clean, maintainable, and well-tested code using TypeScript for type safety and scalability on both the client and server.
• Collaborate with product managers, designers, and other engineers to translate business requirements into technical solutions.
• Collaborate with other team members to set technical standards, establish best practices, and make architecture decisions.
• Actively research and evaluate new technologies, tools, and methodologies to improve the engineering process.
• Demonstrate and articulate a practical understanding of AI tools (e.g., planning, code generation, intelligent testing frameworks) in daily engineering tasks, including their effective application and inherent limitations.

Qualifications

• 5+ years of experience in full-stack software development.
• Expert-level proficiency with TypeScript, including complex type definitions and advanced language features.
• Strong experience with server-side development, including building and consuming RESTful APIs or GraphQL services (proficiency with Hono Framework is a plus).
• Proficiency with relational and non-relational databases
• Familiarity with modern CI/CD pipelines, containerization (Docker), and cloud platforms (primarily AWS, with experience in GCP and/or Azure a plus).
• Preferred, but not required: Proficiency with React and its ecosystem (e.g., Hooks, Context API, Next.js, or similar frameworks). Experience with Angular (any version) in a professional capacity is a plus.

AI and the Evolution of Software Engineering & Ops

All candidates must be prepared to discuss and demonstrate the following during the interview process:

• Practical AI Tool Usage: Specific examples of AI tools used in professional or personal projects to enhance productivity, solve complex problems, or accelerate development. If you have a preferred agentic tool setup, please share!
• Understanding of AI Limitations: A clear understanding and articulation of the current technical, ethical, and accuracy limitations of modern AI tools in the engineering context.
• Strategic AI Opportunity: A viewpoint on how AI tools create new opportunities for software engineering, such as shifting focus from boilerplate code to complex problem-solving or architectural design.
• Evolution of the Engineering Role: A well-articulated point of view on how your role has already changed (e.g., new workflows, skills, ways of collaborating) due to the introduction of AI and how you expect the role to evolve in the coming years based on your assessment of coming advancements in AI tools and technologies.

Salary Range $135,000 - $175,000

Application Process

A cover letter is required. Your cover letter should be informed by the “AI and Forward-Looking Requirements” section above.

The hiring process includes:

• Initial Screening Call
• A Technical Assessment sent by email and returned by email
• A Panel Interview

The Role

As a Senior Full Stack Engineer, you will be a key leader across the entire software development lifecycle, from conceptual design to deployment and monitoring. You will be responsible for building robust, scalable backend services using Python and AWS Serverless technologies (Lambda, DynamoDB, SQS, EventBridge), developing event-sourced systems that provide complete state history and auditability.

A critical component of this role is a demonstrated fluency with modern AI/ML development tools (e.g., GitHub Copilot, Claude Code, agentic coding tools, large language models). We are looking for candidates who not only use these tools daily but can articulate a clear, thoughtful perspective on their limitations, security implications, and the strategic opportunities they create for the engineering profession.

Key Responsibilities

• Lead the design and implementation of highly scalable, cost-efficient serverless backend services using Python and AWS (Lambda, API Gateway, DynamoDB, SQS, EventBridge).
• Architect and build event-sourced systems and event-driven pipelines, ensuring reliable message processing, idempotency, and eventual consistency across distributed services.
• Collaborate with product managers and designers to translate requirements into technical designs and shippable code.
• Implement best practices for security, logging, monitoring, and infrastructure-as-code (e.g., Terraform or CloudFormation).
• Perform rigorous code reviews, mentor junior and mid-level engineers, and drive technical excellence across the team.
• Actively research, propose, and integrate new technologies and patterns, with a focus on optimizing development velocity and system performance.
• Clearly articulate a professional point of view on how to effectively, securely, and ethically integrate AI tools into the software development lifecycle.

Qualifications

Required

• 5+ years of professional experience in full-stack software development.
• Expert-level proficiency in Python for backend development.
• Strong working proficiency with Node.js.
• Deep practical experience designing, deploying, and maintaining applications using serverless architectures (preferably AWS Lambda, API Gateway, and managed services).
• Hands-on experience with DynamoDB, including single-table design patterns, GSI/LSI strategies, and performance optimization at scale.
• Solid understanding of event sourcing and event-driven architecture patterns, including experience with message brokers or streaming services (e.g., SQS, SNS, EventBridge, or Kinesis).
• Experience with CI/CD pipelines, automated testing, and Infrastructure-as-Code.
• Demonstrated Fluency in AI-Assisted Development: Candidates must be able to demonstrate practical, hands-on experience using AI-powered coding tools to achieve specific, quantifiable productivity gains, while also clearly understanding and mitigating the associated risks (e.g., code quality, security, IP concerns).

Nice to Have

• Experience with advanced AWS services (e.g., Kinesis, SageMaker, Step Functions).
• Familiarity with TypeScript for robust front-end or Node.js development.
• Proficiency with a modern front-end framework (e.g., React, Vue, or Angular).
• Experience working in a regulated or compliance-focused environment.
• A Bachelor’s or Master’s degree in Computer Science or a related technical field.

AI and the Evolution of Software Engineering & Ops

All candidates must be prepared to discuss and demonstrate the following during the interview process:

• Practical AI Tool Usage: Specific examples of AI tools used in professional or personal projects to enhance productivity, solve complex problems, or accelerate development. If you have a preferred agentic tool setup, please share!
• Understanding of AI Limitations: A clear understanding and articulation of the current technical, ethical, and accuracy limitations of modern AI tools in the engineering context.
• Strategic AI Opportunity: A viewpoint on how AI tools create new opportunities for software engineering, such as shifting focus from boilerplate code to complex problem-solving or architectural design.
• Evolution of the Engineering Role: A well-articulated point of view on how your role has already changed (e.g., new workflows, skills, ways of collaborating) due to the introduction of AI and how you expect the role to evolve in the coming years based on your assessment of coming advancements in AI tools and technologies.

Application Process

To apply, please submit your resume and a cover letter. Your cover letter should be informed by the “AI and Forward-Looking Requirements” section above.

The hiring process includes:

• Initial screening email
• A Technical Assessment Interview
• A Panel Interview

Salary Range $140,000 - $175,000