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.

Location

This role requires working from our downtown Toronto office 4 days/week (Mon, Tues, Thurs, Fri). Candidates must be based within a 50-mile commuting distance of the office.

About the Role

At Opendoor, AI isn’t a side project - it’s how we work. Across the company, teams default to AI to solve problems, ship faster, and remove friction from everything we do. You will help define the future of how we work by building AI powered workflows, automation, and experiences that drive leverage across Finance — spanning month-end close, SEC Reporting, FP&A, Technical Accounting, Tax, Procurement, Accounts Payable, and Payroll. This is high agency work in high ambiguity - turning messy problems into clean solutions, prototyping fast, and shipping.

You'll make systems design and tooling decisions that affect how our Finance operations scale – so we need people who think critically about what and why they build, the impact it will have on our team, and how to measure success. 

We're looking for AI-native builders who know how to automate complex operational workflows. The accounting and finance domain knowledge can be learned — what matters most is that you're wired to build, that you default to AI in how you approach problems, and that you can map messy business processes into clean, automated systems. 

Why Join Us

• Build AI automation for our Financial Operations from the ground up
• Work on cutting-edge systems directly impacting key Finance processes in a public company 
• Collaborate with talented engineers and finance team members
• Access to enterprise AI tools — Claude Code, Cursor, and LLM APIs. We invest heavily in AI infrastructure so you can build and experiment.

What You'll Do

This is a hands-on individual contributor role. You will design, build, and ship automations — not just evaluate tools or write strategy decks.

• Turn complex Accounting and Finance problems into clear system designs, experiments, and implementation plans
• Build and maintain AI-powered automation that improves operational efficiency, accuracy, and scale across Finance functions
• Automate workflows (journal entries, reconciliations, flux analysis) using SQL, Python, and agentic AI
• Maintain clean, auditable data throughout automated workflows, with dashboards and controls that support both operational and compliance needs
• Partner with the internal SOX team and external auditors to ensure automated processes meet compliance standards and are well-documented
• Build and scale AI literacy across the Finance team through runbooks, documentation, best practices, and hands-on training 

What You'll Bring

• At least 5+ years of work experience building automation, operational workflows, or data systems in any industry. 
• Familiarity with LLM deployment, context engineering and comfortable writing SQL or Python code
• Understanding of machine learning lifecycle concepts: training, evaluation, deployment, monitoring

Systems Thinking: You understand how data flows through operational systems. You can look at a business process, identify the inputs, outputs, dependencies, and failure modes, and design automation around it.

System Design: You take complex, messy problems and reduce them to simple, durable architecture. 

Communication: Articulate problems clearly to both technical and non-technical audiences. You write clean documentation, build dashboards that tell a story, and can walk a stakeholder through your design rationale.

AI Alchemy: You have high agency and a tinkering mindset. You default to experimenting, running variations with new tools and methods - LLMs, automation platforms, coding assistants until you can transmute data into high quality results. You're comfortable writing SQL code, working with APIs, and stitching tools together to ship solutions fast.

Impact Driven: You optimize for impact over novelty, choosing the right tools for the job and ensure performance, scalability and resiliency.

Bonus if you have:

• Experience in Accounting or Finance 
• Comfort working in regulated or compliance-sensitive environments

Tools and Technologies

You'll work across a range of tools and we expect this list to evolve. Ideal candidates will have experience with the following tech stack:

• AI coding assistants: Claude Code, Cursor, or similar 
• Workflow automation: Gumloop or similar platforms
• MCP integrations
• Agentic AI frameworks or building automation flows 
• Data / ERP platforms: Snowflake, NetSuite, Ramp or similar 

Note: Opendoor provides enterprise-level access to all AI tools listed above. Our engineers currently consume billions of AI tokens per month across the company and are not constrained by token limits or personal account restrictions.

Compensation

Our compensation plan consists of a base salary and Opendoor equity  in addition to a comprehensive package of benefits including paid time off, paid holidays, medical/dental/vision insurance, basic life insurance, and 401(k) to eligible employees.  All compensation parameters are based on experience.

 #LI-DM

#LI-Onsite

ABOUT ROCKET MONEY 🔮

Rocket Money’s mission is to meaningfully improve the financial prosperity of millions of people. Rocket Money offers members a unique understanding of their finances and a suite of valuable services that save them time and money – ultimately giving them a leg up on their financial journey.

ABOUT THE TEAM 🤝

Data Platform Engineers at Rocket Money further our mission by building and maintaining the infrastructure that enables our company to understand our users and products through reliable, scalable data systems. We build the foundational platform that ingests, processes, and serves data—enabling our Data Analytics, Machine Learning, and Software Engineering teams to build data products efficiently. We work closely with engineering teams to ensure data is captured correctly at the source, design resilient pipelines, and create self-service capabilities that empower stakeholders.

The Data Platform team is in an exciting phase of growth and formalization. While we have established tools and processes in place (dbt, BigQuery, Terraform), we're actively building the comprehensive standards, practices, and systems that will scale with Rocket Money as it grows. We're looking for engineers who can take ownership and evolve workflows into reliable, well-documented, production-grade systems. This is an opportunity to shape architectural decisions, establish team practices, and define how Rocket Money works with data for years to come.

We have a strong preference for process-oriented systems thinkers who excel in balancing stakeholder requirements, technical debt, and organizational complexity—and who thrive in environments where they need to create structure from ambiguity. You'll need to be comfortable making principled decisions, taking ownership not just of code but of outcomes, and operating with significant autonomy as we build the platform together.

ABOUT THE ROLE 🤹

In this role, you will:

• Be an end-to-end owner of our data platform infrastructure, ensuring its security, usability, and performance. Work closely with analytics engineers, machine learning engineers, and software engineers to ensure the platform meets their needs.
• Make collaborative decisions about data tooling, pipeline design, and governance, and implement opinionated interfaces that facilitate easy and best-practice-aligned development for other teammates.
• Continuously improve failure rates for data sources by moving alerting “to the left”; i.e. catching and quarantining bugs/failures as close to the source as possible.
• Analyze patterns in how source data is generated, modeled, and consumed. Work with stakeholders to implement the best solution when new data sources are added.
• Take ownership of existing tools and workflows that may be functional but lack formal structure, documentation, or reliability measures. You'll assess what's working, identify gaps, and systematically improve systems to production-grade quality.
• Document everything you build knowing that you're creating the foundation others will build upon. Your runbooks, architecture decision records, and system documentation will become the institutional knowledge of our data platform.
• Proactively communicate with multiple stakeholders on platform capabilities, technical constraints, architectural decisions, project priorities, and platform support.
• Confidently juggle multiple projects and priorities in our fast-paced environment and work with stakeholders and platform teammates to ensure infrastructure changes, migrations, and improvements are delivered on schedule.
• Automate aggressively and deliberately; anything from GitHub Actions to Slack Workflows to minimize repetitive tasks. Effectively judge when the level of effort is appropriate and avoid over-engineering.

ABOUT YOU 🦄

• You have 6+ years of experience working with data infrastructure, data engineering, or platform engineering within a fast-paced environment. You are highly proficient with SQL, Python, and cloud-based Infrastructure-as-Code (e.g. Terraform), and comfortable working with bash/shell scripting.
• You have 4+ years of production experience with modern data stacks including data warehouses (BigQuery, Snowflake, or Redshift), orchestration tools, managed ingestion services, and infrastructure as code (Terraform, Pulumi, or CloudFormation).
• You have 2+ years of experience building and maintaining production data pipelines, whether through ELT tools, custom applications, streaming systems, or event-driven architectures.
• You've successfully "professionalized" data infrastructure before—taking scrappy, working systems and evolving them into reliable, well-documented, production-grade platforms. You can articulate what "production-ready" means in a data context.
• You have a bias toward action and aren't paralyzed by imperfect solutions. You understand when "good enough for now with a plan to improve" beats "perfect but six months late." You ship incrementally and iterate based on feedback.
• You're comfortable being the first person to tackle a problem. You don't need extensive mentorship or detailed tickets—you can take a high-level business need and figure out the technical approach. That said, you know when to ask for help and can articulate what you need.
• You take ownership seriously—not just of writing code, but of outcomes. When you build something, you implement monitoring, write runbooks, create alerts, and ensure it can be maintained by others. You think about the full lifecycle of systems, not just initial delivery.
• You have strong opinions, weakly held. You can make and defend architectural decisions, but you're open to feedback and willing to change course when presented with better information. You can disagree and commit.
• You understand that "building from scratch" doesn't mean rejecting existing tools—it means thoughtfully selecting, configuring, and integrating managed services and open-source solutions to create a cohesive platform. You know when to build and when to buy.
• You have experience making big changes to critical data infrastructure. You’ve successfully re-architected, migrated, or upgraded data tooling that has strict SLA’s, without significantly affecting downstream stakeholders.

Bonus points if:

• You have led a data infrastructure migration or modernization project where you defined the vision, approach, and implementation.
• You have created internal tools, frameworks, or CLIs that improved how teams work with data (not just one-off scripts).
• You have established data platform best practices like CI/CD workflows, testing frameworks, or observability standards where none existed.
• Expertise in cloud platforms and technologies analogous to our stack:
  • Our stack: GCP (BigQuery, Datastream, Cloud Functions, Vertex AI, GCS), dbt, Fivetran, Postgres, Python, Terraform, Looker, Retool
  • Analogous experience: AWS (Redshift, DMS, Lambda, SageMaker, S3) or Azure (Synapse, Data Factory, Functions), Snowflake, Airbyte/Stitch, infrastructure as code tools, BI platforms

WE OFFER 💫

• Health, Dental & Vision Plans
• Life Insurance
• Long/Short Term Disability
• Competitive Pay
• 401k Matching
• Team Member Stock Purchasing Program (TMSPP)
• Learning & Development Opportunities
• Tuition Reimbursement
• Unlimited PTO
• Daily Lunch, Snacks & Coffee (in-office only)
• Commuter benefits (in-office only)

Additional information: Salary range of $160,000 - $200,000 + bonus + benefits. Base pay offered may vary depending on job-related knowledge, skills, and experience.

Rocket Money, Inc. is an Affirmative Action and Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Role overview

At ASM, the Software Engineering team works on delivering software that has immediate, tangible results visible in the operation of semiconductor processing equipment hardware. The hardware includes robotics, gas valves, temperature controllers and other hardware. Come join our team and have the opportunity to:

• Develop Advance software for cutting edge tech
• See your work have real results by driving the most advanced HW in the SEMI industry
• Work with a global team full of talented Software Engineers
• Solve complex problems using AI/ML/Advanced Algorithms/Data Science
• Be part to the team that leads the next generation of SEMI manufacture control Software technology and trends
• Travel globally and visit major chip makers FAB sites
• Work in Phoenix, the heart of the next SEMI tech hub

Note: This role is intended for candidates who are graduating in Spring 2026 or have graduated within the past two years and have 0–2 years of professional work experience.

Responsibilities

• Design, develop, test, deploy, maintain and improve software for our semiconductor manufacturing equipment
• Developing for Windows and Windows Real-time Operating Systems
• Troubleshoot and resolve computer software issues, including real-time software control systems
• Able to triage mechanical, electrical and software bugs
• Responsible to manage escalation calls with field support engineers and customers at a national and global level
• Work with QA / Support team to add replicated bugs to regression
• Author, revise, and review system specifications, software designs, test plans, and other software documentation.
• Investigate both internal and external inquiries, questions and problem reports. Offer problem analysis, solutions, or alternatives as a result of these investigations.
• Evaluate software engineering tools.
• Participate in system design teams.
• Travel to customer sites to support installations, training, and troubleshooting of ASM products.
• Develop schedules for software development efforts.
• Provide engineering solutions to resolve all software issues
• Evaluating new software and hardware tools for possible department use

Minimum Qualifications

• Strong software development skills in C++ 
• 1+ years’ experience as a generalist or mid-stack software development with a Bachelor's degree OR recently graduated with Masters degree in Computer Science, Computer Engineering or Computer Systems
• Graduating in Fall 2025 or graduated within the past two years
• 0–2 years of professional work experience

Preferred Qualifications

• Strong software development skills in C++ and C#
• Educational background in Computer Science or Computer Systems
• Experience working with multiple items listed below
  • Software for Machine Control (including Semiconductor equipment) 
  • Developing for Windows and Windows Real-time Operating Systems
  • Multi-threaded applications
  • Real-time software
  • Graphical User Interfaces
  • Device drivers or other interrupt driven software preferred
  • Data Communications and Networking
  • Knowledge of programming tools such as text editors, debuggers, application builders and configuration management tools.
  • Ability to read code and understand the functionality implemented and the ability to translate the functionality into another piece of software
  • Comprehend software documentation including specification and design documents, communication interface specific and API description

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