About the Team

The Enterprise Engineering team builds and maintains the internal tools and platforms that power Roku's business operations, from accounting and finance systems to partner management and content operations. We work at the intersection of technology and business, delivering full-stack web applications that enable Roku to operate at scale. Our team values pragmatic engineering, high-quality test coverage, and leveraging AI to ship faster without sacrificing reliability.

About the Role

We are looking for a Senior Software Engineer with deep backend expertise in TypeScript/Node.js to join our Enterprise Engineering Web Applications team. You will design, build, and maintain backend services and APIs that support Roku's first-party enterprise tools with a focus on the accounting and finance domain. You'll also contribute to frontend development using modern frameworks and own end-to-end quality through test automation.

This is an AI-first engineering role. You will be expected to integrate AI tools and agentic workflows into your daily development process, using them to accelerate delivery, improve code quality, and build smarter internal tools.

What You'll Be Doing

• Design and implement backend services and APIs in TypeScript/Node.js
• Build and maintain full-stack enterprise applications supporting accounting, finance, and business operations
• Architect solutions that are reliable, maintainable, and scalable for internal business-critical workflows
• Own end-to-end test automation by building and maintaining E2E test suites
• Collaborate with finance and accounting stakeholders to translate business requirements into technical solutions
• Use AI coding tools (Claude, Copilot, OpenCode, etc.) as core parts of your development workflow
• Build and improve internal developer tooling, automation, and agentic workflows
• Participate in technical design discussions, and mentoring of team members

We're Excited If You Have

• 7+ years of relevant software development experience
• Strong backend development expertise in TypeScript and Node.js, with Java and Python experience nice-to-have
• Experience building and shipping production web applications with modern frameworks (React, Next.js, or similar)
• Hands-on experience with end-to-end test automation frameworks (Playwright, Cypress, or similar)
• Experience with relational databases (PostgreSQL, MySQL) and data modeling
• Experience with cloud platforms (AWS, GCP, or Azure)
• Experience with Kubernetes
• Experience in a globally distributed team

#LI-JB6

About the team

With so many people using Roku’s products globally, we’ve become well-known for products that “just work” right out of the box and integrate almost by magic.  That doesn’t happen by accident, which is why we are committed to making sure our products aren’t just intuitive; they’re obvious.  To support that commitment, the Roku’s Automation support and Tools team focuses on providing innovative and impactful tools that improve efficiency, enhance productivity of all engineering to test Roku products, from industry’s most reliable streaming media platform to smart home products that seamlessly integrate with Roku entertainment OS for a great connected home user experience. We accomplish this using state of the art technology and engineering to make it happen, with consideration for the customer as the centre of all that we do.

Roku’s embedded software automation and tools team has an excellent opportunity for a Senior Software Engineer with strong experience in building automation framework and tools for embedded devices. The role involves developing and maintaining software and tools that help various internal teams to test and manage Roku’s products. Working closely with internal stakeholders to enhance existing automation toolset with new capabilities and advanced features that empower all engineering and accelerate validation efforts for SW releases. 

About the role

You will work cross-functionally with various engineering teams, using your automation tooling expertise to help both firmware developers and QA to create and deliver the highest quality products that provide valuable end-user feedback to improve customer experience. This position requires Python expertise with strong experience using web frameworks, excellent debugging, written, and organizational skills. You will be joining a talented, high-performance team of developers with a history of delivery. We are looking for someone who can help us maintain this pace and continue delivering high quality as we grow. 

We are looking for a keen problem solver and a self-motivated individual with excellent communication and collaborative skills who is eager to learn and grow in the consumer electronics space. As an engineer on the team, you will require the skills and confidence to undertake the challenges of working in a fast-paced environment, frequently be taken out of your comfort zone, and relish getting your hands dirty working with user-facing products. 

What you will be doing:

• Develop and release new E2E automation support and tools 
• Debug issues to improve the quality of automated test tools and frameworks 
• Conduct code reviews to improve code quality and optimization 
• Promote coding conventions and standards for code re-usability and cleanliness 
• Document feature guides, identify and formulate user requirements, and define product behavior 
• Support and maintain existing automation tools and technology 
• Mentor less experienced engineers and drive automation development 
• Assist in monitoring and maintenance of critical systems 
• Champion the adoption of AI tools and technologies to enhance automation capabilities and team productivity. 
• Review and provide technical feedback on design documents and high-level architecture diagrams across multiple tools and teams, with a focus on evaluating design trade-offs, scalability, maintainability, and alignment with overall system architecture. 

We're excited if you have:

• 10+ years of hands-on experience with automation systems 
• 10+ years of programming experience, preferably with Python 
• Bachelor’s degree in computer science or related field 
• Proficient in Linux, Python-based test automation frameworks, and tools using REST APIs 
• Hands-on experience in development/integration of E2E test automation frameworks and tools for embedded software devices 
• Proficient use of AI tools and technologies with a proven track record as a promoter and advocate for AI adoption in software development and testing automation. 
• Agentic workflow familiarity: Working knowledge of multi-step AI orchestration frameworks and the practical use of AI agents to support and streamline day-to-day development workflows. 
• Experienced in developing and maintaining web-based tools using JavaScript and React/Next.js 
• Experience with DevOps and continuous integration tools (Jenkins, GitLab CI, Docker, and Kubernetes) 
• Experience with CI/CD pipeline development and deployment via AWS or GCP cloud technologies 
• Experience with unit testing frameworks – pytest/pyunit and Cypress for UI testing 
• Experience developing web applications using Flask, FastAPI, Django, and Nginx 
• Knowledge in using AI for increasing test automation coverage and productivity 
• Experience with retail Consumer Electronic (CE) devices, ideally in the Over The Top (OTT) streaming domain 
• Expert problem-solving and technical troubleshooting skills 
• Ability to learn new technologies quickly 
• A self-directed professional able to work independently 
• Ability to work through ambiguous requirements and be flexible/adaptable to change 
• Comfortable and experienced working with cross-functional peers and internal stakeholders across European and US time zones 
• Excellent communication and collaborative skills 

Additional nice to have skills: 

• Previous experience with Non-Functional Testing (Performance Testing, Stress Testing) 
• Knowledge of network technologies and libraries such as TCP/IP and HTTP 
• Experience with database technologies (MySQL, PostgreSQL, MongoDB, Redis) for test data management 
• Familiarity with monitoring and observability tools (Grafana, Prometheus, ELK stack, Datadog) 
• Knowledge of streaming protocols and technologies (HLS, DASH, RTMP, WebRTC) 
• Experience with API testing tools (Postman, REST Assured, GraphQL) 
• Understanding of security testing principles and tools (OWASP, penetration testing) 
• Experience with mobile testing frameworks and cross-platform testing 
• Familiarity with test reporting and analytics platforms (Allure, TestRail, ReportPortal) 
• Experience with infrastructure as code (Terraform, Ansible, CloudFormation) 
• Knowledge of machine learning concepts for test optimization and predictive analysis 
• Familiarity with Agile/Scrum methodologies and project management tools (Jira, Confluence) 
• Basic understanding of hardware debugging tools and techniques for embedded systems 

#LI-AB3

About the team

With so many people using Roku’s products globally, we’ve become well-known for products that “just work” right out of the box and integrate almost by magic. That doesn’t happen by accident, which is why we are committed to making sure our products aren’t just intuitive, they’re obvious.  To support that commitment, the Roku’s Automation support and Tools team focuses on providing innovative and impactful tools that improve efficiency, enhance productivity of all engineering to test Roku products, from industry’s most reliable streaming media platform to smart home products that seamlessly integrate with Roku entertainment OS for a great connected home user experience. We accomplish this using state of the art technology and engineering to make it happen, with consideration for the customer as the centre of all that we do.

About the role

The Roku’s software automation and tools team has an excellent opportunity for a Senior Software Engineer with strong experience in building automation framework and tools for SW embedded devices. The role involves developing and maintaining software and tools that help various internal teams to test and manage Roku’s products. Working closely with internal stakeholders to enhance existing automation toolset with new capabilities and advanced features that empower all engineering and accelerate validation efforts for SW releases.

You will work cross-functionally with various engineering teams, using your finest automation expertise to help both FW developers and QA to create and deliver highest quality product that help in provide valuable end-user feedback to improve customer’s experience.  This position requires python expertise with strong experience of using web frameworks, excellent debugging, written and organizational skills. You will be joining a talented, high-performance team of developers with a history of delivery.  We are looking for someone who can help us keep up this pace and continue delivering high quality as we grow.

We are looking for a keen problem solver and a self-motivated individual with excellent communication and collaborative skills who is eager to learn and grow in consumer electronics space. As an engineer on the team you will require skills and confidence to undertake the challenges of working in a fast-paced environment, frequently be taken out of your comfort zone and relish getting your hands dirty working with user facing products

What you'll be doing

• Support and maintain existing automation tools and technology
• Develop and release new E2E automation support and tools
• Debug issues to improve the quality of automated test tools and frameworks
• Conduct code reviews to improve code quality and optimization
• Promote coding conventions and standards for code re-usability and cleanliness
• Document Feature guides, identify and formulate user requirements, product behavior
• Mentor less experienced engineers and driving automation development
• Assist in monitoring and maintenance of critical systems

We're excited if you have

• 5+ years of hands-on experience with automation systems
• 5+ years of programming experience, preferably with Python
• Bachelor’s degree in Computer Science or related
• Proficient in linux, Python based test automation frameworks and tools using REST APIs
• Hands on experience in development/integration of E2E test automation framework and tools for embedded software devices
• Experienced in developing and maintaining web based tools using Javascript, React
• Proficiency with DevOps, continuous integration tools (Jenkins, Gitlab CI, Teamcity, Docker and Kubernetes)
• Experience with CI/CD pipeline development and deployment via AWS or GCP cloud technologies
• Experience with Unit Testing frameworks – pytest/pyunit and cypress, playwright for UI testing
• Experience of developing web applications using Flask, FastAPI, Django, Nginx
• Experience and knowledge of using generative AI
• Expert problem-solving and technical troubleshooting skills
• Ability to learn new technologies quickly
• A self-directed professional able to work independently
• Ability to work through ambiguous requirements and being flexible/adaptable to change
• Comfortable and experienced working with cross-functional peers and internal stakeholders across European and US timezones
• Excellent communication and collaborative skills
• Experience with retail Consumer Electronic (CE) devices, ideally in the Over The Top (OTT) streaming domain
• Previous experience with Non-Functional Testing (Performance Testing, Stress Testing)
• Knowledge of network technologies and libraries such as TCP/IP and HTTP
• Previous experience and knowledge of image processing and inferencing, creating computer vision capabilities for visual testing

#LI-AB3

About the Team 

The DMP team plays a critical role in Roku’s Advertising organization, leading initiatives around audience management that power decision-making across the advertising ecosystem. We develop and manage products that enable advanced segmentation and audience management for advertisers while meeting the operational needs of internal teams. 

We work closely with Product Managers, Machine Learning, Ad Sales, Ads Operations, and multiple groups within Advertising Engineering to deliver high-impact solutions.  

Looking ahead, we are exploring AI-driven capabilities to further enhance the effectiveness of advertising campaigns and improve operational efficiency of our platforms. 

About the Role 

We are seeking a highly skilled Senior Software Engineer with deep expertise in big data technologies, including Apache Spark and Apache Airflow. This hybrid position bridges software engineering and data engineering, requiring the ability to design, build, and maintain scalable systems for both application development and large-scale data processing. 

In this role, you will collaborate with cross-functional teams to architect and manage robust, production-grade data products and APIs that power critical capabilities across the advertising platform. You will work with technologies such as Apache Spark, Apache Airflow, ScyllaDB/Cassandra, Aerospike, Kubernetes, and SpringBoot to deliver reliable, high-performance solutions. 

The ideal candidate is a proactive, self-motivated professional with a strong track record in building high-scale data services and a dedication to delivering exceptional results. 

What You’ll Be Doing 

Software Development 

• Design and build APIs and backend services using Spring Boot to support data products and audience management workflows. 

• Write clean, maintainable, and efficient code, ensuring adherence to best practices through code reviews. 

Big Data Engineering 

• Design, develop, and maintain data pipelines and ETL workflows using Apache Spark and Apache Airflow. 

• Optimize data storage, retrieval, and processing systems to ensure reliability, scalability, and performance. 

• Develop and fine-tune complex queries using Apache Spark for large-scale datasets. 

• Monitor, troubleshoot, and improve data systems to minimize downtime and maximize efficiency. 

API and Platform Development

• Design, Development, and maintain large scale, low latency API systems using SpringBoot and Kubernetes

• Maintain NoSQL Infrastructure including ScyllaDB and Aerospike

Collaboration & Mentorship 

• Partner with the machine learning team, software engineers, and other teams to deliver integrated, high-quality solutions. 

• Provide technical guidance and mentorship to junior engineers, promoting best practices in software and data engineering. 

We’re Excited If You Have 

• 8+ years of experience in software and/or data engineering with expertise in big data technologies such as Apache Spark, Apache Airflow. 

• Expertise with at least one of the following ScyllaDB and Aerospike (preferred). 

• Strong understanding of SOLID principles and distributed systems architecture. 

• Proven experience in distributed data processing, data warehousing, and real-time data pipelines. 

• Advanced SQL skills, with expertise in query optimization for large datasets. 

• Exceptional problem-solving abilities and the capacity to work independently or collaboratively. 

• Excellent verbal and written communication skills. 

• Experience with cloud platforms such as AWS, GCP, or Azure, and containerization tools like Docker and Kubernetes. (preferred) 

• Experience in AdTech, in advertising data platforms and audience management. (preferred)

• Strong programming skills in Python, Java, and/or Scala. (preferred) 

• Knowledge of CI/CD pipelines, DevOps practices, and infrastructure-as-code tools (e.g., Jenkins & Terraform). (preferred) 

• Expertise in data modeling, schema design, and data visualization tools. Experience with building Agentic AI systems to automate decision-making and enhance analytics workflows. (preferred) 

• Bachelor's degree in computer science, Engineering, or a related field (or equivalent experience). 

#LI-GL1

About the Team 

The DMP team plays a critical role in Roku’s Advertising organization, leading initiatives around audience management that power decision-making across the advertising ecosystem. We develop and manage products that enable advanced segmentation and audience management for advertisers while meeting the operational needs of internal teams. 

We work closely with Product Managers, Machine Learning, Ad Sales, Ads Operations, and multiple groups within Advertising Engineering to deliver high-impact solutions.  

Looking ahead, we are exploring AI-driven capabilities to further enhance the effectiveness of advertising campaigns and improve operational efficiency of our platforms. 

About the Role 

We are seeking a highly skilled Senior Software Engineer with deep expertise in big data technologies, including Apache Spark and Apache Airflow. This hybrid position bridges software engineering and data engineering, requiring the ability to design, build, and maintain scalable systems for both application development and large-scale data processing. 

In this role, you will collaborate with cross-functional teams to architect and manage robust, production-grade data products and APIs that power critical capabilities across the advertising platform. You will work with technologies such as Apache Spark, Apache Airflow, ScyllaDB/Cassandra, Aerospike, Kubernetes, and SpringBoot to deliver reliable, high-performance solutions. 

The ideal candidate is a proactive, self-motivated professional with a strong track record in building high-scale data services and a dedication to delivering exceptional results. 

What You’ll Be Doing 

Software Development 

• Design and build APIs and backend services using Spring Boot to support data products and audience management workflows. 

• Write clean, maintainable, and efficient code, ensuring adherence to best practices through code reviews. 

Big Data Engineering 

• Design, develop, and maintain data pipelines and ETL workflows using Apache Spark and Apache Airflow. 

• Optimize data storage, retrieval, and processing systems to ensure reliability, scalability, and performance. 

• Develop and fine-tune complex queries using Apache Spark for large-scale datasets. 

• Monitor, troubleshoot, and improve data systems to minimize downtime and maximize efficiency. 

API and Platform Development

• Design, Development, and maintain large scale, low latency API systems using SpringBoot and Kubernetes

• Maintain NoSQL Infrastructure including ScyllaDB and Aerospike

Collaboration & Mentorship 

• Partner with the machine learning team, software engineers, and other teams to deliver integrated, high-quality solutions. 

• Provide technical guidance and mentorship to junior engineers, promoting best practices in software and data engineering. 

We’re Excited If You Have 

• 8+ years of experience in software and/or data engineering with expertise in big data technologies such as Apache Spark, Apache Airflow. 

• Expertise with at least one of the following ScyllaDB and Aerospike (preferred). 

• Strong understanding of SOLID principles and distributed systems architecture. 

• Proven experience in distributed data processing, data warehousing, and real-time data pipelines. 

• Advanced SQL skills, with expertise in query optimization for large datasets. 

• Exceptional problem-solving abilities and the capacity to work independently or collaboratively. 

• Excellent verbal and written communication skills. 

• Experience with cloud platforms such as AWS, GCP, or Azure, and containerization tools like Docker and Kubernetes. (preferred) 

• Experience in AdTech, in advertising data platforms and audience management. (preferred)

• Strong programming skills in Python, Java, and/or Scala. (preferred) 

• Knowledge of CI/CD pipelines, DevOps practices, and infrastructure-as-code tools (e.g., Jenkins & Terraform). (preferred) 

• Expertise in data modeling, schema design, and data visualization tools. Experience with building Agentic AI systems to automate decision-making and enhance analytics workflows. (preferred) 

• Bachelor's degree in computer science, Engineering, or a related field (or equivalent experience). 

#LI-GL1

About the Team 

The Ads Analytics team plays a critical role in Roku’s Advertising organization, leading measurement and analytics initiatives that power decision-making across the advertising ecosystem. We develop and manage products that deliver actionable insights for advertisers while meeting the operational and analytical needs of internal business teams. 

We work closely with Product Managers, Ad Sales, Ad Operations, Data Science, and multiple other software teams within the Advertising Engineering organization to deliver high-impact solutions.  

Looking ahead, we are exploring AI-driven measurement capabilities to further enhance the effectiveness of advertising campaigns and strengthen internal analytics. 

About the Role 

We are seeking a high skilled Senior Software Engineer with deep expertise in API Development using Spring Boot while also possessing knowledge of Apache Spark-based Big Data pipelines using Airflow. This hybrid position bridges software engineering and data engineering, requiring the ability to design, build, and maintain scalable systems for both application development and large-scale data processing. 

You will communicate and collaborate heavily with both business and engineering to ensure high quality standards and overall project delivery success. In this role, you will collaborate with cross-functional teams to architect and manage robust, production-grade data products that power critical analytics and measurement capabilities. You will work with technologies such as Apache Spark, Apache Airflow, Trino, Druid, Spring Boot, StarRocks, and Looker to deliver reliable, high-performance solutions. 

The ideal candidate is a proactive, self-motivated professional with a strong track record in building applications and services with a dedication to delivering exceptional results. 

What You’ll Be Doing 

Software Development 

• Design and build APIs and backend services using Spring Boot to support data products and analytics workflows. 

• Write clean, maintainable, and efficient code and tests, ensuring adherence to best practices through code reviews. 

Big Data Engineering 

• Design, develop, and maintain data pipelines and ETL workflows using Apache Spark and Apache Airflow. 

• Optimize data storage, retrieval, and processing systems to ensure reliability, scalability, and performance. 

• Develop and fine-tune complex queries and analytics solutions using Druid, Trino, and StarRocks for large-scale datasets. 

• Monitor, troubleshoot, and improve data systems to minimize downtime and maximize efficiency. 

Collaboration & Mentorship 

• Partner with data scientists, software engineers, and other teams to deliver integrated, high-quality solutions. 

• Provide technical guidance and mentorship to junior engineers, promoting best practices in software and data engineering. 

We’re Excited If You Have 

• 8+ years of experience in software and/or data engineering with expertise in big data technologies such as Apache Spark, Apache Airflow. 

• Expertise with at least one of the following: Apache Druid, StarRocks, and Trino. 

• Strong understanding of SOLID principles and distributed systems architecture. 

• Proven experience in distributed data processing, data warehousing, and real-time data pipelines. 

• Strong programming skills in Java, Python, or Scala.

• Advanced SQL skills, with expertise in query optimization for large datasets. 

• Expertise in data modeling, schema design, and data visualization tools.

• Experience building highly scalable, low-latency, APIs.

• Exceptional problem-solving abilities and the capacity to work both independently and collaboratively as needed. 

• Exceptional verbal and written communication skills. 

• Experience with cloud platforms such as AWS, GCP, or Azure, and containerization tools like Docker and Kubernetes. (preferred) 

• Experience in AdTech, in advertising data platforms and campaign measurement. (preferred)

• Knowledge of CI/CD pipelines, DevOps practices, and infrastructure-as-code tools (e.g., Terraform). (preferred) 

• Experience with building Agentic AI systems to automate decision-making and enhance analytics workflows. (preferred)  

• Bachelor's degree in computer science, Engineering, or a related field (or equivalent experience). 

About the Team 

The Ads Analytics team plays a critical role in Roku’s Advertising organization, leading measurement and analytics initiatives that power decision-making across the advertising ecosystem. We develop and manage products that deliver actionable insights for advertisers while meeting the operational and analytical needs of internal business teams. 

We work closely with Product Managers, Ad Sales, Ad Operations, Data Science, and multiple other software teams within the Advertising Engineering organization to deliver high-impact solutions.  

Looking ahead, we are exploring AI-driven measurement capabilities to further enhance the effectiveness of advertising campaigns and strengthen internal analytics. 

About the Role 

We are seeking a high skilled Senior Software Engineer with deep expertise in API Development using Spring Boot while also possessing knowledge of Apache Spark-based Big Data pipelines using Airflow. This hybrid position bridges software engineering and data engineering, requiring the ability to design, build, and maintain scalable systems for both application development and large-scale data processing. 

You will communicate and collaborate heavily with both business and engineering to ensure high quality standards and overall project delivery success. In this role, you will collaborate with cross-functional teams to architect and manage robust, production-grade data products that power critical analytics and measurement capabilities. You will work with technologies such as Apache Spark, Apache Airflow, Trino, Druid, Spring Boot, StarRocks, and Looker to deliver reliable, high-performance solutions. 

The ideal candidate is a proactive, self-motivated professional with a strong track record in building applications and services with a dedication to delivering exceptional results. 

What You’ll Be Doing 

Software Development 

• Design and build APIs and backend services using Spring Boot to support data products and analytics workflows. 

• Write clean, maintainable, and efficient code and tests, ensuring adherence to best practices through code reviews. 

Big Data Engineering 

• Design, develop, and maintain data pipelines and ETL workflows using Apache Spark and Apache Airflow. 

• Optimize data storage, retrieval, and processing systems to ensure reliability, scalability, and performance. 

• Develop and fine-tune complex queries and analytics solutions using Druid, Trino, and StarRocks for large-scale datasets. 

• Monitor, troubleshoot, and improve data systems to minimize downtime and maximize efficiency. 

Collaboration & Mentorship 

• Partner with data scientists, software engineers, and other teams to deliver integrated, high-quality solutions. 

• Provide technical guidance and mentorship to junior engineers, promoting best practices in software and data engineering. 

We’re Excited If You Have 

• 8+ years of experience in software and/or data engineering with expertise in big data technologies such as Apache Spark, Apache Airflow. 

• Expertise with at least one of the following: Apache Druid, StarRocks, and Trino. 

• Strong understanding of SOLID principles and distributed systems architecture. 

• Proven experience in distributed data processing, data warehousing, and real-time data pipelines. 

• Strong programming skills in Java, Python, or Scala.

• Advanced SQL skills, with expertise in query optimization for large datasets. 

• Expertise in data modeling, schema design, and data visualization tools.

• Experience building highly scalable, low-latency, APIs.

• Exceptional problem-solving abilities and the capacity to work both independently and collaboratively as needed. 

• Exceptional verbal and written communication skills. 

• Experience with cloud platforms such as AWS, GCP, or Azure, and containerization tools like Docker and Kubernetes. (preferred) 

• Experience in AdTech, in advertising data platforms and campaign measurement. (preferred)

• Knowledge of CI/CD pipelines, DevOps practices, and infrastructure-as-code tools (e.g., Terraform). (preferred) 

• Experience with building Agentic AI systems to automate decision-making and enhance analytics workflows. (preferred)  

• Bachelor's degree in computer science, Engineering, or a related field (or equivalent experience). 

About the team

The Advertising Performance group focuses on performance for all participants in the Advertising ecosystem - Advertisers, Publishers and Roku. The systems and solutions span across different disciplines and technologies to perform realtime multi-objective optimization with distributed systems at large scale and low latencies. We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems and Auction Dynamics to solve a large set of complex problems. At the core of this is our Machine Learning, Experimentation and Inference Platform that powers the entire landscape which we continuously evolve over time.

About the role 

In this role you will build teams focused on the Ads Auction and Marketplace to optimize yield, gross profit, perform realtime multi-objective optimization across various short and long term objectives, build control and simulation systems, design and run experiments and extend the experimentation framework. 

You will partner closely with other Engineering, Inventory and Product teams to define the vision and strategy for your group and to build and deliver the roadmap.

What you’ll be doing

• Lead the design, implementation, and evolution of real-time ads auction systems powering Roku’s CTV advertising across The Roku Channel and the Roku platform.
• Own and enhance core auction capabilities including ad pod construction, bid evaluation, ranking, pricing, pacing, budget enforcement, and frequency capping.
• Build low-latency, highly reliable distributed services that operate at massive scale, serving billions of ad opportunities with strict latency and uptime requirements.
• Design auction logic that balances viewer experience (ad load, relevance, repetition) with advertiser performance, publisher yield, and platform revenue.
• Develop and optimize SSP-side auction mechanisms, integrating with multiple DSPs, programmatic demand sources, and direct-sold campaigns.
• Partner closely with product managers, data science, ads research teams to translate marketplace and monetization goals into scalable technical solutions.
• Drive yield optimization through auction design, demand shaping, floor strategies, and pricing experiments.
• Lead experimentation using A/B testing, auction simulations, and offline replay frameworks, and make data-driven decisions based on performance metrics and statistical rigor.
• Ensure auction correctness, fairness, explainability, and transparency, while maintaining compliance with privacy, regulatory, and brand-safety requirements.
• Influence the long-term technical roadmap for Roku Ads by proposing architecture improvements, scalability strategies, and performance optimizations.

We are excited if you have

• 5+ years of experience building large-scale distributed systems
• 5+ years working with cloud-based platforms and infrastructure
• Deep experience in building microservices using Java for container platforms such as Docker or Kubernetes
• Solid understanding of databases SQL and NoSQL
• Hands-on Experience working with AWS, GCP or similar cloud services
• Experience with a breadth of protocols and data formats such as REST, WebSockets, HTTPS, JSON, and Protobuf
• Demonstrated ability to drive timely consensus in design with other senior team members
• Bachelors or Master's degree in Computer Science, Engineering, or equivalent

#LI-MS3

About the team

The Advertising Performance group focuses on performance for all participants in the Advertising ecosystem - Advertisers, Publishers and Roku. The systems and solutions span across different disciplines and technologies to perform realtime multi-objective optimization with distributed systems at large scale and low latencies. We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems and Auction Dynamics to solve a large set of complex problems. At the core of this is our Machine Learning, Experimentation and Inference Platform that powers the entire landscape which we continuously evolve over time.

About the role 

In this role you will build teams focused on the Ads Auction and Marketplace to optimize yield, gross profit, perform realtime multi-objective optimization across various short and long term objectives, build control and simulation systems, design and run experiments and extend the experimentation framework. 

You will partner closely with other Engineering, Inventory and Product teams to define the vision and strategy for your group and to build and deliver the roadmap.

What you’ll be doing

• Lead the design, implementation, and evolution of real-time ads auction systems powering Roku’s CTV advertising across The Roku Channel and the Roku platform.
• Own and enhance core auction capabilities including ad pod construction, bid evaluation, ranking, pricing, pacing, budget enforcement, and frequency capping.
• Build low-latency, highly reliable distributed services that operate at massive scale, serving billions of ad opportunities with strict latency and uptime requirements.
• Design auction logic that balances viewer experience (ad load, relevance, repetition) with advertiser performance, publisher yield, and platform revenue.
• Develop and optimize SSP-side auction mechanisms, integrating with multiple DSPs, programmatic demand sources, and direct-sold campaigns.
• Partner closely with product managers, data science, ads research teams to translate marketplace and monetization goals into scalable technical solutions.
• Drive yield optimization through auction design, demand shaping, floor strategies, and pricing experiments.
• Lead experimentation using A/B testing, auction simulations, and offline replay frameworks, and make data-driven decisions based on performance metrics and statistical rigor.
• Ensure auction correctness, fairness, explainability, and transparency, while maintaining compliance with privacy, regulatory, and brand-safety requirements.
• Influence the long-term technical roadmap for Roku Ads by proposing architecture improvements, scalability strategies, and performance optimizations.

We are excited if you have

• 5+ years of experience building large-scale distributed systems
• 5+ years working with cloud-based platforms and infrastructure
• Deep experience in building microservices using Java for container platforms such as Docker or Kubernetes
• Solid understanding of databases SQL and NoSQL
• Hands-on Experience working with AWS, GCP or similar cloud services
• Experience with a breadth of protocols and data formats such as REST, WebSockets, HTTPS, JSON, and Protobuf
• Demonstrated ability to drive timely consensus in design with other senior team members
• Bachelors or Master's degree in Computer Science, Engineering, or equivalent

#LI-MS3

About the Role 

We are building a next-generation observability and cloud platform that is high-performance, cost-efficient, secure, and scalable across multi-region, multi-cloud clusters. You will lead the architecture and evolution of Roku’s observability and cloud infrastructure stack. This includes metrics, logs, traces, telemetry pipelines, service mesh, developer experience, and reliability of systems that power thousands of services and millions of devices. 

You will drive a vision where developers gain deep visibility with minimal overhead, onboarding is seamless, and insights are available in real time. Your work will directly help Roku scale efficiently while maintaining reliability, cost control, and performance. 

What You’ll Be Doing 

• Architect and lead Roku’s observability platform across metrics, logs, and traces; evolve data pipelines and storage layers optimized for high throughput, performance, and cost at Roku scale (TSDBs, Parquet, distributed processing). 

• Extend and harden open‑source observability systems; overhaul core components (e.g., storage layers, query paths) to improve performance, reliability, and usability at scale. 

• Implement features such as pre‑aggregation, down-sampling, and sampling to reduce load and accelerate queries across the platform. 

• Collaborate across platform, SRE, and product teams to migrate hundreds of workloads to our common platform; augment and automate CI/CD flows and onboarding. 

• Integrate security into infrastructure and platform services; ensure robust multi‑tenant, multi‑cluster, and multi‑cloud designs. 

• Contribute improvements back to open source and CNCF‑aligned projects; shape standards adoption (OpenTelemetry, OpenMetrics) across the company. 

• Mentor engineers; establish best practices for reliability, efficiency, and cost management across service mesh and observability domains. 

What You'll have  

• Extensive experience with  software engineering with a track record of architecting distributed systems or platforms at scale. 

• Strong hands‑on experience in Golang and one scripting language (e.g., Python or Shell). 

• Experience operating observability at pb-scale ingestion and hundreds of millions of series. 

• Expertise in observability platforms and tooling (Prometheus, Grafana, Loki, Tempo, ELK/OpenSearch, ClickHouse) and standards (OpenTelemetry, OpenMetrics).  

• Deep experience building systems of scale and operating cloud infrastructure with Kubernetes; strong proficiency with service mesh technologies (Istio/Envoy), infrastructure‑as‑code (Terraform) and experience in multi‑cloud (AWS, GCP) 

• Demonstrated ability to evolve storage and query architectures for cost, scale, and latency (e.g., TSDB, Parquet, distributed processing). 

• Proven experience integrating security as part of infrastructure and platform development.   

• Exceptional cross‑functional communication; effective collaboration with both technical and non‑technical stakeholders. 

• Culture fit: independent thinker, pragmatic problem‑solver, low‑ego collaborator who moves fast and focuses on company success. 

• Experience integrating AI tools to improve processes and reduce toil. 
• Open‑source contributions in CNCF projects is preferred but not mandatory.  

#LI-PA1

About the team 

The Ads Analytics team plays a critical role in Roku’s Advertising organization, leading measurement and analytics initiatives that power decision-making across the advertising ecosystem. We develop and manage products that deliver actionable insights for advertisers while meeting the operational and analytical needs of internal business teams.  

We work closely with Product Managers, Ad Sales, Ad Operations, Data Science, and multiple other software teams within the Advertising Engineering organization to deliver high-impact solutions.   

Looking ahead, we are exploring AI-driven measurement capabilities to further enhance the effectiveness of advertising campaigns and strengthen internal analytics. 

About the role 

We are seeking a high skilled Senior Software Engineer with deep expertise in API Development using Spring Boot while also possessing knowledge of Apache Spark-based Big Data pipelines using Airflow. This hybrid position bridges software engineering and data engineering, requiring the ability to design, build, and maintain scalable systems for both application development and large-scale data processing.  

You will communicate and collaborate heavily with both business and engineering to ensure high quality standards and overall project delivery success. In this role, you will collaborate with cross-functional teams to architect and manage robust, production-grade data products that power critical analytics and measurement capabilities. You will work with technologies such as Apache Spark, Apache Airflow, Trino, Druid, Spring Boot, StarRocks, and Looker to deliver reliable, high-performance solutions.  

The ideal candidate is a proactive, self-motivated professional with a strong track record in building applications and services with a dedication to delivering exceptional results. 

What you’ll be doing  

Software Development  

• Design and build APIs and backend services using Spring Boot to support data products and analytics workflows.  
• Write clean, maintainable, and efficient code and tests, ensuring adherence to best practices through code reviews.  

Big Data Engineering  

• Design, develop, and maintain data pipelines and ETL workflows using Apache Spark and Apache Airflow.  
• Optimize data storage, retrieval, and processing systems to ensure reliability, scalability, and performance.  
• Develop and fine-tune complex queries and analytics solutions using Druid, Trino, and StarRocks for large-scale datasets.  
• Monitor, troubleshoot, and improve data systems to minimize downtime and maximize efficiency.  

Collaboration & Mentorship  

• Partner with data scientists, software engineers, and other teams to deliver integrated, high-quality solutions.  
• Provide technical guidance and mentorship to junior engineers, promoting best practices in software and data engineering. 

We’re excited if you have  

• 10+ years professional software development experience. 
• Experience building highly scalable, low-latency REST services and API frameworks. 
• Able to efficiently write SQL queries and analyze results to explore business problems and inquiries.
• Ability to translate queries and reporting requirements into production-level data processing pipelines.
• Proficient in day-to-day use of Python / Java / Scala.
• Strong understanding of and experience with distributed computing frameworks like Hive/Hadoop and Apache Spark.
• Expertise in data modeling, schema design, and data visualization tools. 
• Experience working in GCP and/or AWS is a plus.
• Experience with JavaScript, Node.js and React is nice to have.
• Experience deploying services on Kubernetes is a plus. 
• Knowledge of CI/CD pipelines, DevOps practices, and infrastructure-as-code tools (e.g., Terraform) is a plus. 
• Background in computer science or similar quantitative field. 

About the team

You will be part of the Roku Video Platform Engineering team and responsible for building the next-generation video services for the Roku Cloud TV Platform. Roku pioneered TV streaming and continues to innovate and lead the industry. The Roku Channel has us well-positioned to help shape the future of streaming. Continued success relies on investing in the Roku Cloud TV Platform to deliver a high-quality streaming TV experience on a global scale. 

About the role

As a Video Encoding Engineer, you will build, optimize, and maintain high-performance video processing workflows. You will own our end-to-end encoding toolchain—from experimentation and profile tuning to automated packaging workflows—ensuring our content is delivered with maximum quality, reliability, and efficiency.

You will work closely with the team on key video services projects around video ingestion, encoding, VoD/live-linear, Server-Side Ads Insertion, and Video QoS, with the goal of delivering a best-in-class streaming TV experience across all Roku devices. The projects that you will work on will impact millions of Roku users around the world. Throughout, you will have the opportunity to collaborate with key product engineering stakeholders across Roku engineering teams and to lead the design of our video services platform.

The ideal candidate will have endless curiosity and can pair a global mindset with locally relevant execution. You should be a gritty problem solver and self-starter who can drive programs with the product and commercial teams within Roku and across external strategic partner organizations. The successful candidate will display a balance of hard and soft skills, including the ability to respond quickly to changing business needs. 

What you’ll be doing

• Design, build, optimize, and maintain FFmpeg-based encoding pipelines for both VOD and Live workflows, operating at scale in cloud environments such as AWS or GCP
• Develop, refine, and validate encoding presets for modern codecs, including H.264, HEVC, and AV1, ensuring optimal quality-to-bitrate performance
• Implement advanced encoding strategies such as multi-pass workflows, CRF tuning, per-title optimizations, and quality-targeted encoding
• Benchmark and evaluate video quality using VMAF and other objective metrics to drive continuous improvements in efficiency and viewing experience
• Build and maintain adaptive streaming packaging workflows, including HLS, DASH, and CMAF, ensuring broad device compatibility and reliable playback
• Profile and optimize system performance by identifying and eliminating bottlenecks across compute, storage, and I/O layers
• Write, review, and improve code, assessing architectural tradeoffs to deliver secure, high-performance, and highly concurrent video infrastructure services
• Collaborate cross-functionally with engineering, product, and platform teams to support and advance company-wide video service initiatives

We’re excited if you have

• Strong problem-solving and analytical abilities
• 5+ years of solid programming experience and passionate about writing high-quality and well-architected code
• Expert-level knowledge of FFmpeg or Gstreamer and their related toolchains (filters, flags, debugging, custom builds)
• Experience with hardware-based encoder/decoder libraries (NVENC, Vulkan
• Strong understanding of compression theory, codec internals, GOP structures, bitrate control, etc
• Experience with container formats: MP4, TS, fragmented MP4, ISOBMFF
• Familiarity with HLS/DASH, CMAF, adaptive bitrate design, DRM, and SCTE 35
• A track record working with applied AI-based video enhancement and compression algorithms (Super Resolution, Denoising, Artifact Removal)
• Hands-on experience with cloud compute (AWS Lambda/ECS/Batch, GCP, Kubernetes, or similar)
• Ability to handle periodic on-call duty as well as out-of-band requests; strong written and verbal communication skills
• Bachelor's degree in computer science plus 8 years of experience or equivalent; Master's degree preferred 

#LI-SB-5

About the Team

The Advanced Development team at Roku pushes beyond today’s product lines to invent the next generation of intelligent and generative media systems.
We explore ideas that sit years ahead of production, developing foundational technologies that will redefine how content is understood, created, and personalised across millions of Roku devices.

This is a rare environment — a PhD-level, cross-disciplinary group combining machine learning research, software engineering, and DevOps.
Everyone here is an expert, but not narrowly focused. The team blends deep technical mastery with broad creative vision — people who challenge convention, embrace ambiguity, and build what’s never been built before. It’s a collaborative, low-ego, ownership-driven culture built on trust and curiosity.

We’re seeking an Applied Scientist with a strong foundation in mathematics, machine learning, and computer science, combined with experience in cloud engineering, DevOps, and computer vision — someone who thrives where research meets production.

About the Role

As a Senior Applied Machine Learning Engineer, you’ll help design, build, and deploy the systems that make media smarter.
You’ll work across the full model and software lifecycle, from prototype to production, developing scalable ML pipelines and cloud architectures that power generative AI, intelligent media understanding, content analysis, and advertising intelligence.

You’ll operate at the intersection of machine learning, infrastructure, and software engineering, taking ownership from data collection through deployment — and seeing your work directly influence how audiences experience Roku’s content and advertising ecosystem.

What You’ll Be Doing

• Deploying scalable, fault-tolerant computer vision, media understanding, and generative AI systems to production

• Overseeing the full model development cycle: ideation, prototyping, implementation, deployment, testing, and operations

• Designing uncertainty metrics and communicating results to both technical and non-technical stakeholders

• Gathering and compiling datasets, defining annotation ontologies, auditing annotation operations, and ensuring data quality

• Staying up to date with industry and academic trends in computer vision, machine learning, and generative models for media and advertising

• Working closely with product and other engineering teams to implement new content and advertising experiences through cloud services

• Integrating services from other teams around the company, while also providing reusable ML services to others

• Evaluating and providing feedback on new platform technologies provided by internal teams

• Working with QA teams to address bugs and contribute to automation and quality assurance

We’re Excited If You Have

• A Master’s degree (PhD preferred) in Computer Science, Applied Mathematics, or a related field

• Strong background developing applied machine learning systems using PyTorch or TensorFlow

• Expertise in image processing, computer vision, or natural language processing

• Experience using AWS, GCP, or Azure for storing data, training, and serving models

• Proven ability to evaluate models and communicate insights effectively

• Experience building APIs with frameworks such as GraphQL or REST

• Experience with workflow orchestration tools such as Airflow, Argo, AWS Step Functions, or Metaflow

• Hands-on experience with Docker, Kubernetes, Terraform, CloudFormation, CI/CD automation, and Python build or packaging tools

#LI-PA1

About The Team 

The Roku trust engineering team is a close knit group of professionals with a passion for information security.  Our mission is to protect our customers, partners, devices, services, infrastructure, and data. We work collaboratively, sharing insights and expertise to stay ahead of the curve. Join us, and you’ll be part of a dynamic team that thrives on challenges and celebrates victories together. 

About The Role  

As a Senior Security Engineer on the Trust Cloud team, your role involves evaluating, architecting, designing, and implementing end-to-end security controls to impact the global user base. A key focus is on developing automated, scalable security solutions to enhance efficiency and protect Roku. This position requires a broad breadth of security expertise across all disciplines of security, including networking, DevSecOps, security tooling implementation, policy and procedure, risk evaluation, etc. 

What You Will Be Doing 

• Conducting enterprise, network, and application level security reviews.
• Conducting threat modelling for infrastructure, platform, and application initiatives.
• Planning and overseeing execution of security initiatives and projects
• Partnering with infrastructure, platform, and application teams to embed security into application architectures and deployment workflows as part of a robust Secure Software Development Lifecycle (SSDLC).
• Improving IAM policies, network configurations, DNS security, and cloud resource management practices.
• Designing and implementing integrations with third-party security platforms to automate vulnerability management, secure secret handling, and cloud posture monitoring, ensuring findings are actionable and seamlessly integrated into engineering workflows.
• Responding to security incidents to triage, contain, remediate, and report.
• Leveraging AI to accelerate your learning and enhance your work products.
• Driving security initiatives end-to-end — from identifying risks to delivering solutions — with high autonomy in a fast-moving environment.
• Automating vulnerability detection, misconfiguration checks, and compliance validation across cloud and containerised environments.
• Creating reusable security automation modules, templates, and patterns for engineering teams to adopt. 

We're Excited If You Have

• Experience doing security consulting and have balanced experience doing hands on implementation
• Experience supporting/leading DevSecOps initiatives and assisting teams in utilising and onboarding onto DSO platforms
• Designing, building, operating, and maintaining DSO platforms through IaC
• Offensive cyber operations such as application, system, and network level penetration testing
• Software Engineering experience with at least one general purpose programming language (ex. Python, Golang, C, Rust, etc.)
• Developed and/or implemented data tagging, data catalogs, or other data protection related activities
• Experience designing and administering enterprise identity and access management solutions at scale (ex: AD, EntraID, Okta, etc)
• Experience securely running and operating web applications, web services, and service-oriented architecture in production environments.
• A proven track record of deploying and operating Kubernetes clusters in production.  
• Experience deploying and operating infrastructure in multiple cloud providers (AWS, GCP, Azure)
• Fleet administration of Linux workstations and servers
• Defensive cyber operations such as operating a SEIM, managing a SOC, or leading cyber investigations 

#LI-AM3

About The Team 

The Roku trust engineering team is a close knit group of professionals with a passion for information security.  Our mission is to protect our customers, partners, devices, services, infrastructure, and data. We work collaboratively, sharing insights and expertise to stay ahead of the curve. Join us, and you’ll be part of a dynamic team that thrives on challenges and celebrates victories together. 

About The Role  

As a Senior Security Engineer on the Trust Cloud team, your role involves evaluating, architecting, designing, and implementing end-to-end security controls to impact the global user base. A key focus is on developing automated, scalable security solutions to enhance efficiency and protect Roku. This position requires a broad breadth of security expertise across all disciplines of security, including networking, DevSecOps, security tooling implementation, policy and procedure, risk evaluation, etc. 

What You Will Be Doing 

• Conducting enterprise, network, and application level security reviews.
• Conducting threat modelling for infrastructure, platform, and application initiatives.
• Planning and overseeing execution of security initiatives and projects
• Partnering with infrastructure, platform, and application teams to embed security into application architectures and deployment workflows as part of a robust Secure Software Development Lifecycle (SSDLC).
• Improving IAM policies, network configurations, DNS security, and cloud resource management practices.
• Designing and implementing integrations with third-party security platforms to automate vulnerability management, secure secret handling, and cloud posture monitoring, ensuring findings are actionable and seamlessly integrated into engineering workflows.
• Responding to security incidents to triage, contain, remediate, and report.
• Leveraging AI to accelerate your learning and enhance your work products.
• Driving security initiatives end-to-end — from identifying risks to delivering solutions — with high autonomy in a fast-moving environment.
• Automating vulnerability detection, misconfiguration checks, and compliance validation across cloud and containerised environments.
• Creating reusable security automation modules, templates, and patterns for engineering teams to adopt. 

We're Excited If You Have

• Experience doing security consulting and have balanced experience doing hands on implementation
• Experience supporting/leading DevSecOps initiatives and assisting teams in utilising and onboarding onto DSO platforms
• Designing, building, operating, and maintaining DSO platforms through IaC
• Offensive cyber operations such as application, system, and network level penetration testing
• Software Engineering experience with at least one general purpose programming language (ex. Python, Golang, C, Rust, etc.)
• Developed and/or implemented data tagging, data catalogs, or other data protection related activities
• Experience designing and administering enterprise identity and access management solutions at scale (ex: AD, EntraID, Okta, etc)
• Experience securely running and operating web applications, web services, and service-oriented architecture in production environments.
• A proven track record of deploying and operating Kubernetes clusters in production.  
• Experience deploying and operating infrastructure in multiple cloud providers (AWS, GCP, Azure)
• Fleet administration of Linux workstations and servers
• Defensive cyber operations such as operating a SEIM, managing a SOC, or leading cyber investigations 

#LI-AM3

About the team

Our team’s mission is to build cutting-edge technology that facilitates experimentation and enables data-driven decisions, such as those for Roku. Our team provides an end-to-end solution, from intuitive management interfaces and a robust, highly scalable backend to a sophisticated data insights framework.

We are a globally distributed team with presence in the US and Europe. We value technical expertise, creativity, a strong sense of ownership and collaboration.

About the role 

At Roku, we’re building and evolving a large-scale experimentation platform that powers data-driven decision-making across the organsation. Our system supports 5,000+ experiments per year, serves 100+ million devices, and processes over 100,000 operations per second—all while maintaining high reliability and low latency.

In this role, you’ll help shape the next generation of our distributed backend. You’ll design and implement new platform capabilities such as bias avoidance mechanisms, advanced segment management, and experiment orchestration features that ensure trustworthy results at scale. At the same time, you’ll work on strengthening the system’s resilience, performance, and scalability, tackling challenges that come with high throughput and global reach.
You’ll collaborate closely with engineers, data scientists, and product partners to translate experimentation needs into robust, production-ready systems. This is a hands-on role with real impact: the work you do will directly influence how teams across the company run experiments, learn faster, and make better decisions.

What you’ll be doing

• Build and evolve high-throughput, low-latency distributed backend services in Java that power Roku’s experimentation platform at massive scale.

• Design and implement core experimentation capabilities (e.g. bias avoidance, advanced segmentation, experiment orchestration) to ensure statistically sound results across millions of users.

• Strengthen system resilience, scalability, and performance, operating reliably at 100k+ ops/sec and across 100M+ devices globally.

• Partner closely with data scientists, product, and platform engineers to translate experimentation needs into production-ready backend systems with real business impact.

We’re excited if you have 

• Degree in Computer Science or equivalent
• Expertise in Java and Spring Boot for developing robust backend applications.
• Strong knowledge of object-oriented design principles and distributed software architectures.
• Proven experience in building and maintaining solutions using both NoSQL and relational databases.
• Solid understanding and practice of test-driven development (TDD) and test automation frameworks.
• Familiarity with statistical concepts and their application within software systems.
• Demonstrated ability to design, develop, and test high-performance distributed systems.
• Experience with AWS cloud services (e.g., EC2, S3, Lambda).
• Familiarity with Istio and Kubernetes for managing microservices and container orchestration.
• Understanding of A/B testing methodologies and experience with experimentation platforms is a plus

This is a hands-on, high-impact role for someone who thrives in an environment where innovation meets engineering excellence. You’ll collaborate with a world-class team of software and hardware engineers, contributing across the entire lifecycle of building, optimising, and delivering next-generation intelligent systems.

#LI-MS3

Are you passionate about building scalable, high-performance systems that process massive amounts of data? Do you thrive on designing and implementing innovative solutions to empower engineering teams with actionable insights? Are you excited to advance open-source observability at a massive scale? Join us to extend (open source) observability tools and build new capabilities that help teams manage data better and get actionable insights. 

About the Team 

The Observability team is part of Roku’s Cloud Technology Infrastructure organisation and plays a critical role in our platform. We are a high-performing, fast-moving international team that thrives on ownership, effective communication, and delivering impactful engineering solutions. 

Our mission is to advance Roku’s observability platform, which operates at an impressive scale by ingesting terabytes of data daily and managing hundreds of millions of active series. As part of this mission, we focus on building scalable, performant systems to meet Roku’s unique needs. By leveraging open-source tools, CNCF-supported projects, and custom solutions, we enable engineering teams across Roku to monitor, debug, and optimise their applications with ease. 

What sets us apart is our results-driven culture rooted in ownership, accountability, and fast iteration. We prioritise solving meaningful engineering problems, fostering collaboration, and continuously improving how we work as a team. 

About the Role 

You will work on core observability systems (metrics, logs, traces) while also developing robust data pipelines and storage solutions optimized for high throughput, performance, and cost. You’ll leverage technologies such as time-series databases (TSDB), columnar storage formats (e.g., Parquet), and distributed data processing frameworks to advance the platform’s capabilities. Collaboration with cross-functional teams will be critical, as you’ll integrate observability into Roku’s cloud-native stack and contribute improvements back to the open-source community. 

• Extend and integrate open-source observability systems, and when needed, structurally overhaul core components, such as storage layers and query paths, to improve performance, reliability, and usability of these tools at scale. 

• Build services to improve performance, usability, reliability, and cost efficiency. 

• Implement features like pre-aggregation, downsampling, and sampling to reduce load and accelerate queries. 

• Create developer-facing capabilities for metrics, logs, and traces usage, data quality, and cost management. 

• Automate onboarding, dashboards, alerting, and tracing. 

• Collaborate across platform and infrastructure teams to integrate observability into Roku’s cloud-native stack. 

What We’re Looking For 

• Extensive experience in software engineering building distributed, high-throughput systems or observability platforms. 

• Hands on Go experience; our observability ecosystem is Go-based, making it the most effective language for this role. 

• Experience with, or strong interest in, observability tools (Prometheus, Grafana, Loki, Tempo, ELK/OpenSearch, Clickhouse) and standards (OpenTelemetry, OpenTracing, OpenMetrics). 

• Deep understanding of distributed systems and data models 

• Hands-on experience with Kubernetes, and cloud platforms (AWS, GCP, Azure). 

#LI-PA1

Are you passionate about building scalable, high-performance systems that process massive amounts of data? Do you thrive on designing and implementing innovative solutions to empower engineering teams with actionable insights? Are you excited to advance open-source observability at a massive scale? Join us to extend (open source) observability tools and build new capabilities that help teams manage data better and get actionable insights. 

About the Team 

The Observability team is part of Roku’s Cloud Technology Infrastructure organisation and plays a critical role in our platform. We are a high-performing, fast-moving international team that thrives on ownership, effective communication, and delivering impactful engineering solutions. 

Our mission is to advance Roku’s observability platform, which operates at an impressive scale by ingesting terabytes of data daily and managing hundreds of millions of active series. As part of this mission, we focus on building scalable, performant systems to meet Roku’s unique needs. By leveraging open-source tools, CNCF-supported projects, and custom solutions, we enable engineering teams across Roku to monitor, debug, and optimise their applications with ease. 

What sets us apart is our results-driven culture rooted in ownership, accountability, and fast iteration. We prioritise solving meaningful engineering problems, fostering collaboration, and continuously improving how we work as a team. 

About the Role 

You will work on core observability systems (metrics, logs, traces) while also developing robust data pipelines and storage solutions optimized for high throughput, performance, and cost. You’ll leverage technologies such as time-series databases (TSDB), columnar storage formats (e.g., Parquet), and distributed data processing frameworks to advance the platform’s capabilities. Collaboration with cross-functional teams will be critical, as you’ll integrate observability into Roku’s cloud-native stack and contribute improvements back to the open-source community. 

• Extend and integrate open-source observability systems, and when needed, structurally overhaul core components, such as storage layers and query paths, to improve performance, reliability, and usability of these tools at scale. 

• Build services to improve performance, usability, reliability, and cost efficiency. 

• Implement features like pre-aggregation, downsampling, and sampling to reduce load and accelerate queries. 

• Create developer-facing capabilities for metrics, logs, and traces usage, data quality, and cost management. 

• Automate onboarding, dashboards, alerting, and tracing. 

• Collaborate across platform and infrastructure teams to integrate observability into Roku’s cloud-native stack. 

What We’re Looking For 

• Extensive experience in software engineering building distributed, high-throughput systems or observability platforms. 

• Hands on Go experience; our observability ecosystem is Go-based, making it the most effective language for this role. 

• Experience with, or strong interest in, observability tools (Prometheus, Grafana, Loki, Tempo, ELK/OpenSearch, Clickhouse) and standards (OpenTelemetry, OpenTracing, OpenMetrics). 

• Deep understanding of distributed systems and data models 

• Hands-on experience with Kubernetes, and cloud platforms (AWS, GCP, Azure). 

#LI-PA1

Are you passionate about building scalable, high-performance systems that process massive amounts of data? Do you thrive on designing and implementing innovative solutions to empower engineering teams with actionable insights? Are you excited to advance open-source observability at a massive scale? Join us to extend (open source) observability tools and build new capabilities that help teams manage data better and get actionable insights. 

About the Team 

The Observability team is part of Roku’s Cloud Technology Infrastructure organisation and plays a critical role in our platform. We are a high-performing, fast-moving international team that thrives on ownership, effective communication, and delivering impactful engineering solutions. 

Our mission is to advance Roku’s observability platform, which operates at an impressive scale by ingesting terabytes of data daily and managing hundreds of millions of active series. As part of this mission, we focus on building scalable, performant systems to meet Roku’s unique needs. By leveraging open-source tools, CNCF-supported projects, and custom solutions, we enable engineering teams across Roku to monitor, debug, and optimize their applications with ease. 

What sets us apart is our results-driven culture rooted in ownership, accountability, and fast iteration. We prioritize solving meaningful engineering problems, fostering collaboration, and continuously improving how we work as a team. 

About the Role 

You will work on core observability systems (metrics, logs, traces) while also developing robust data pipelines and storage solutions optimized for high throughput, performance, and cost. You’ll leverage technologies such as time-series databases (TSDB), columnar storage formats (e.g., Parquet), and distributed data processing frameworks to advance the platform’s capabilities. Collaboration with cross-functional teams will be critical, as you’ll integrate observability into Roku’s cloud-native stack and contribute improvements back to the open-source community. 

• Extend and integrate open-source observability systems, and when needed, structurally overhaul core components, such as storage layers and query paths, to improve performance, reliability, and usability of these tools at scale. 

• Build services to improve performance, usability, reliability, and cost efficiency. 

• Implement features like pre-aggregation, downsampling, and sampling to reduce load and accelerate queries. 

• Create developer-facing capabilities for metrics, logs, and traces usage, data quality, and cost management. 

• Automate onboarding, dashboards, alerting, and tracing. 

• Collaborate across platform and infrastructure teams to integrate observability into Roku’s cloud-native stack. 

What We’re Looking For 

• Extensive experience in software engineering building distributed, high-throughput systems or observability platforms. 

• Hands on Go experience; our observability ecosystem is Go-based, making it the most effective language for this role. 

• Experience with, or strong interest in, observability tools (Prometheus, Grafana, Loki, Tempo, ELK/OpenSearch, Clickhouse) and standards (OpenTelemetry, OpenTracing, OpenMetrics). 

• Deep understanding of distributed systems and data models 

• Hands-on experience with Kubernetes, and cloud platforms (AWS, GCP, Azure). 

#LI-PA1

Are you passionate about building scalable, high-performance systems that process massive amounts of data? Do you thrive on designing and implementing innovative solutions to empower engineering teams with actionable insights? Are you excited to advance open-source observability at a massive scale? Join us to extend (open source) observability tools and build new capabilities that help teams manage data better and get actionable insights. 

About the Team 

The Observability team is part of Roku’s Cloud Technology Infrastructure organisation and plays a critical role in our platform. We are a high-performing, fast-moving international team that thrives on ownership, effective communication, and delivering impactful engineering solutions. 

Our mission is to advance Roku’s observability platform, which operates at an impressive scale by ingesting terabytes of data daily and managing hundreds of millions of active series. As part of this mission, we focus on building scalable, performant systems to meet Roku’s unique needs. By leveraging open-source tools, CNCF-supported projects, and custom solutions, we enable engineering teams across Roku to monitor, debug, and optimise their applications with ease. 

What sets us apart is our results-driven culture rooted in ownership, accountability, and fast iteration. We prioritise solving meaningful engineering problems, fostering collaboration, and continuously improving how we work as a team. 

About the Role 

You will work on core observability systems (metrics, logs, traces) while also developing robust data pipelines and storage solutions optimized for high throughput, performance, and cost. You’ll leverage technologies such as time-series databases (TSDB), columnar storage formats (e.g., Parquet), and distributed data processing frameworks to advance the platform’s capabilities. Collaboration with cross-functional teams will be critical, as you’ll integrate observability into Roku’s cloud-native stack and contribute improvements back to the open-source community. 

• Extend and integrate open-source observability systems, and when needed, structurally overhaul core components, such as storage layers and query paths, to improve performance, reliability, and usability of these tools at scale. 

• Build services to improve performance, usability, reliability, and cost efficiency. 

• Implement features like pre-aggregation, downsampling, and sampling to reduce load and accelerate queries. 

• Create developer-facing capabilities for metrics, logs, and traces usage, data quality, and cost management. 

• Automate onboarding, dashboards, alerting, and tracing. 

• Collaborate across platform and infrastructure teams to integrate observability into Roku’s cloud-native stack. 

What We’re Looking For 

• Extensive experience in software engineering building distributed, high-throughput systems or observability platforms. 

• Hands on Go experience; our observability ecosystem is Go-based, making it the most effective language for this role. 

• Experience with, or strong interest in, observability tools (Prometheus, Grafana, Loki, Tempo, ELK/OpenSearch, Clickhouse) and standards (OpenTelemetry, OpenTracing, OpenMetrics). 

• Deep understanding of distributed systems and data models 

• Hands-on experience with Kubernetes, and cloud platforms (AWS, GCP, Azure). 

#LI-PA1

Role & Team

As a Data Engineering Manager, you will lead across several cross-functional teams, managing up to ~10 data engineers and GIS specialists. You will support teams working on data processing and pipelines to enable ML-powered product capabilities.

Our product teams are cross functional and will typically include product managers, designers, engineers and subject matter experts relating to the team’s domain.

You will be accountable for the technical direction and delivery outcomes of your area. You will challenge your teams to pursue ambitious goals while providing a high level of support — growing engineering talent and fostering a highly collaborative, team-based environment where people can do great work.

Your primary focus will be on building high-performing teams and driving results through others. You will not be expected to spend significant time doing hands-on coding; however, you will be expected to dive deep technically when required and leverage your experience to support strong technical decision-making.

Time zone requirement: Europe (GMT/WET, CET, EET) and Eastern North America (NST, AST, EST)

What You'll Do

• Enable our data engineers to become highly productive members of their cross-functional teams, empowering them to ship high-quality, reliable data platforms and pipelines on a daily basis.
• Grow the teams by attracting great talent from your network.
• Foster an inclusive and caring culture where everyone can do their best work.
• Provide regular 1:1 coaching and feedback to tap into the potential of all your team members and help them thrive and reach their aspirations.
• Be a strategic partner to product managers, machine learning engineers, and other stakeholders within your domains and ensure that we are making the correct data architecture and platform decisions that balance short and long term goals.
• Ensure suitability of the data architecture, pipelines, and data models within your domains to enable longer term product, analytics, and machine learning goals.
• Work closely with the other Product & Engineering leaders on strategy, technology and people, including improving our data engineering practices and introducing capabilities that can accelerate data access, reliability, and unlock new product and data-driven opportunities

Skills & Experience

• Experience working in a high growth scaleup environment
• Passionate about climate
• Product minded and able to demonstrate significant impact you have had on a business through the application of data platforms and data-driven systems
• 2+ years experience leading and managing data engineers across multiple teams
• Experience working with the following (or similar) technologies: Python, SQL, data pipeline orchestration tools (e.g., Airflow, Dagster), data warehouses/lakehouses, Postgres DB, data pipelines
• Ability to unblock your team by contributing at a senior engineering level (e.g., reviewing data models, debugging pipelines, guiding architecture). How hands-on you'll be in this role will depend on team size and maturity
• Comfortable working in a build it, run it environment (GCP, cloud run, grafana, k8s) - or similar, with an understanding of data reliability, observability, and pipeline operations
• Strong leadership skills with the ability to mentor and coach engineers at all levels
• Excellent communication skills and ability to collaborate effectively in a cross-functional team environment
• Passion for learning and staying updated with evolving technologies and industry trends, particularly in data engineering and data infrastructure

Nice To Have

• Experience working with maps/imagery/geospatial domains  

Note: We believe that all people are capable of great things. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description.

What We Offer

• Competitive, location-specific compensation and benefits 
• Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around
• Home office stipend, coworking and ongoing education budgets 
• A company culture that genuinely embodies each of our core values
• To be part of truly mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve our climate crisis

Note: if you are an intern, new grad, or staff applicant, please do not apply using this link and visit our jobs page for those specific postings.

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

About the Organization 

The Payments organization focuses on developing products and platforms that enable users to accept payments from customers efficiently. This includes building APIs for processing payments, enabling regional, non-card payment options, and extending Stripe's capabilities to make it easy for businesses to accept in-person payments. The Risk Engineering team develops products that minimize financial and regulatory risks while ensuring a seamless user experience, thereby safeguarding Stripe’s brand and financial stability. 

Team Matching: exact team matching for one of the subteams within this org will begin during final stages. Please note we may also consider you for different orgs based on your experience, location, etc. More information on our team matching process can be found here. 

What you’ll do

We’re looking for Backend engineers who want to make an impact on managing money at a global scale with a passion for building ergonomic APIs. You’ll play a key role in extending our balance management platform and in building out a new funds accessibility platform leveraged by enterprises and SMBs alike. Our team collaborates with many cross-functional teams – from Infrastructure to Product –  at Stripe to deliver innovative solutions that address evolving user needs.

Responsibilities

• Scope, design, build, and maintain APIs, services, and large-scale systems that reliably and efficiently handle billions of money movement requests
• Debug and solve critical production issues across services and multiple levels of the stack
• Mentor engineers to help them grow
• Collaborate with stakeholders across the company to build new features at large-scale, while improving internal engineering standards, tooling, and processes
• Collaborate effectively in a distributed and hybrid team, maintaining open communication and strong connections with colleagues

Who you are

We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 7-12+ years of industry software engineering experience (does not include internships nor includes co-ops)
• Strong coding skills in any programming language (we understand new languages can be learned on the job so our interview process is language agnostic)
• Strong collaboration skills, can work across workstreams within your team and contribute to your peers’ success
• Have the ability to thrive on a high level of autonomy, responsibility, and think of yourself as entrepreneurial
• Interest in working as a generalist across varying technologies and stacks to solve problems and delight both internal and external users

Preferred Qualifications

• Experience with large-scale financial tracking systems
• Good understanding and practical knowledge in cloud based services (e.g. gRPC, GraphQL, Docker/Kubernetes, cloud services such as AWS, etc.) 

Why Verifone

For more than 30 years, Verifone has established a remarkable record of leadership in the electronic payment technology industry. Verifone is one of the leading electronic payment solutions brands and among the largest providers of electronic payment systems worldwide.

Verifone has a diverse, dynamic, and fast-paced work environment in which employees are focused on results and have opportunities to excel. We take pride in working with leading retailers, merchants, banks, and third-party partners to invent and deliver innovative payment solutions around the world. We strive for excellence in our products and services and are obsessed with customer happiness.

Across the globe, Verifone employees are leading the payments industry through experience, innovation, and an ambitious spirit. Whether it’s developing the next generation of secure payment systems or finding new ways to bring electronic payments to emerging markets, the Verifone team is dedicated to the success of our customers, partners, and investors. It is this passion for innovation that drives every Verifone employee toward personal and professional success.

Verifone is proudly an in-office work culture as we see immense benefits to career development and business results from our colleagues being physically co-located.

What’s Exciting About the Role

Verifone is seeking a Kafka DevOps Engineer to join our Platform Engineering team. This is an operations-first role with a strong emphasis on scripting, automation, and pipeline development. You’ll be hands-on with day-to-day Kafka operations, reliability, tuning, and high availability for payment gateway solutions that process billions of transactions annually on-prem and in AWS Cloud. Beyond keeping the lights on, you’ll play a key role in building the data pipelines—of which Kafka is a core component—that power Verifone’s new AI, machine learning, and analytics initiatives. You’ll also be part of an active effort to migrate Kafka and related services to Kubernetes, giving you hands-on experience with a meaningful infrastructure modernization project. The technology footprint is broad: Redis, MongoDB, PostgreSQL, MySQL, Snowflake, and more—so you’ll grow well beyond a single-technology niche.

Key Responsibilities

Kafka Operations & Reliability

• Manage and support Apache Kafka clusters (including MSK), Kafka Connect ecosystem, and KSQL for high-throughput, fault-tolerant messaging and event streaming pipelines.
• Monitor system health, set up alerts, and drive incident response and root cause analysis (RCA).
• Handle day-to-day operational tasks including offset management, lag monitoring, consumer group management, and cluster rebalancing.
• Perform routine cluster maintenance: upgrades, configuration changes, scaling, and health checks.

Scripting, Automation & DevOps

• Develop and manage automation scripts using Python and Shell scripting to reduce manual toil and improve operational efficiency.
• Design, implement, and maintain robust CI/CD pipelines for patching automation.
• Build and maintain Infrastructure as Code (IaC) using tools such as Terraform, Ansible, or similar.
• Containerize and orchestrate workloads using Docker and Kubernetes, with the opportunity to help migrate Kafka and related services to Kubernetes.

Data Pipeline Development

• Build and optimize end-to-end data pipelines, with Kafka as a core streaming component alongside batch and ETL processes, enabling new AI, ML, and analytics use cases.
• Collaborate with development teams to implement best practices for data flow, security, scalability, and performance.
• Continuously identify and implement improvements to the software development lifecycle (SDLC).

Cloud & Infrastructure

• Manage cloud infrastructure on AWS (VMs, networking, storage, IAM, etc.).
• Support cloud migration tasks and assist in moving workloads between on-prem and cloud environments.

Required Qualifications / Skills

• 4+ years of overall engineering experience with 2+ years of hands-on experience supporting Kafka infrastructure in a large-scale production environment.
• Kafka Producer/Consumer microservices concepts and Kafka distributed architecture.
• Solid Linux fundamentals: networking basics, logs, system troubleshooting, process/memory, disk.
• Strong scripting and automation skills (Python, Bash) with a track record of reducing operational toil.
• CI/CD pipeline development and Infrastructure-as-Code experience (Terraform preferred).
• Cloud engineering skills, preferably AWS (EC2, VPC, IAM, MSK/ElastiCache, CloudWatch).
• Familiarity with observability tools (metrics/logs/tracing concepts) and incident response practices.
• Basic understanding of distributed systems tradeoffs (availability, consistency, partitions, backpressure).
• Strong communication and presentation skills with emphasis on executive communication.
• Flexible with regards to working shifts; on-call and weekends.

Preferred Skills (Highly Desired)

Data Engineering & Pipelines

• Data engineering skills including data analytics, data processing, ETL, and data lake technologies (batch and streaming, file formats like Parquet, table formats like Iceberg/Delta/Hudi, basic orchestration).
• Experience with AWS data tools (Athena, Glue, Iceberg, Redshift, etc.).
• Exposure to Kafka Streams, Apache Flink, or similar stream processing frameworks.

Database & Caching Technologies

• Operate Redis deployments for caching, ephemeral state, queues/streams, and rate limiting use cases.
• Relational DB experience: PostgreSQL and/or MySQL (indexing basics, vacuum/analyze, query plans, replication fundamentals).
• MongoDB operational familiarity (replica sets, elections, oplog basics, backup/restore).

Infrastructure & Security

• Container/Kubernetes familiarity (deployments, stateful workloads, storage classes).
• On-prem experience (VMware/KVM, storage, networking).
• Security fundamentals: least privilege, secrets management, encryption-in-transit/at-rest concepts.
• Experience working with PCI (Payment Card Industry Data Security) standards.

What We Offer

• Direct impact on Verifone’s global payment infrastructure—your work keeps billions of transactions flowing reliably every year.
• Ground-floor involvement in building the data pipelines that will drive Verifone’s AI, machine learning, and analytics strategy.
• Hands-on participation in a Kafka-to-Kubernetes migration—a resume-building modernization project from day one.
• Multi-technology exposure—Kafka, Redis, MongoDB, PostgreSQL, MySQL, Snowflake—so you grow as a well-rounded platform engineer, not a single-tool specialist.
• Mentorship from senior engineers and Kafka architects with deep production experience.
• Clear career progression path from mid-level to senior and lead engineer.
• Funded certification paths—Confluent (CCDAK, Certified Administrator), AWS (Solutions Architect, MSK Specialty), CKA—plus budget for courses and technical conferences.
• Hybrid/remote working flexibility with a collaborative team culture.
• Competitive compensation with performance-based incentives.

Our Commitment

Verifone is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. Verifone is also committed to compliance with all fair employment practices regarding citizenship and immigration status.

This senior role focuses on strengthening the quality engineering foundation for our SDK by developing robust automation, scalable CI/CD systems, and effective test strategies. You will work closely with cross-functional partners to enhance test coverage, improve workflows, and ensure reliable delivery across multiple platforms. The role requires strong technical depth, collaborative working, and the ability to drive meaningful impact quickly.

What you’ll be doing

• Designing, implementing, and maintaining CI/CD pipelines to support build, test, and release workflows.
• Developing automation and tooling in Python to streamline test orchestration and system validation.
• Creating and running automated tests across unit, integration, and system layers.
• Debugging and diagnosing issues across build, test, and deployment environments.
• Supporting Linux and Windows development environments and contributing to cross-platform scripting.
• Applying modern test frameworks and quality metrics to improve test strategy and reporting.
• Collaborating closely with multiple SDK teams to align on shared initiatives.
• Participating in rotational assignments to deepen domain expertise and broaden cross-project knowledge.
• Coordinating with teams across London, Bristol, and Dublin, including occasional travel as needed.
• Mentoring peers, sharing best practices, and influencing quality engineering approaches.

What we are looking for

• Experience building and maintaining CI/CD pipelines (Jenkins/Groovy or equivalent).
• Strong Python 3 skills for automation, tooling, and test orchestration.
• Experience developing and executing automated tests at multiple levels.
• Fluency with Linux and Windows development environments.
• Proficiency with scripting languages such as python, bash, or PowerShell.
• Ability to diagnose and resolve issues across complex build and test systems.
• Familiarity with test frameworks such as pytest, GTest, or similar.
• Understanding of software quality metrics, reporting, and test strategy.
• Experience or awareness in one or more additional areas: C/C++, CMake, C#, Rust, .NET, Docker, Kubernetes, VM orchestration, graphics APIs, AIML/MLOps, or desktop app testing.
• Strong communication and collaboration skills, with the ability to work effectively across distributed teams and represent quality engineering perspectives.

Staff Site Reliability Engineer

As a Staff SRE at Obsidian, you will define and drive the company-wide reliability vision for a complex, multi-tenant SaaS platform serving enterprise and financial customers. You will operate as a strategic partner to DevOps and Platform Engineering leadership, shaping a unified reliability strategy that scales across the organization.

Your core mandate: ensure Obsidian detects, diagnoses, and communicates system issues before customers are impacted—consistently and predictably.

This is a hands-on technical role that involves architecting and leading the implementation of systems that handle real-world complexity, including upstream SaaS dependencies, sparse and noisy signals, and mission-critical enterprise workloads.

Key Responsibilities

• Reliability Strategy & Architecture - Define and lead long-term reliability strategy across services. Establish end-to-end system visibility frameworks and guide architecture for observability, detection, and resilience.
• Cross-Org Leadership - Partner across teams to embed reliability, standardize SLI/SLOs, and serve as a technical escalation expert.
• Detection & Observability - Build intelligent detection systems (anomaly detection, connector health models) and enable self-service observability.
• Incident Management - Define and evolve a tiered incident communication strategy, improve response practices, and lead postmortems to strengthen reliability and customer trust.
• Execution - Contribute hands-on to system design, monitoring, and debugging across distributed systems and data pipelines.

Required Qualifications

• 5+ years in SRE, Production Engineering, or related roles
• 3+ years operating at a senior or technical leadership level (Staff or equivalent scope)
• Deep expertise in:
• AWS and/or GCP
• Kubernetes and Helm
• Observability stacks (Prometheus, Grafana, or equivalent)
• CI/CD systems (GitLab CI/CD, ArgoCD, etc.)
• Proven experience designing and scaling reliability systems for multi-tenant SaaS platforms
• Strong debugging and systems thinking across distributed microservices and legacy systems
• Demonstrated ability to lead initiatives that improve incident detection, response, and system resilience
• Hands-on engineering approach with a track record of building—not just configuring—reliability systems

Preferred Qualifications

• Experience in B2B SaaS serving enterprise or financial customers
• Familiarity with third-party SaaS connector architectures and ingestion patterns
• Experience building anomaly detection or intelligent alerting systems
• Experience designing customer-facing status pages and incident communication frameworks

Why This Role

• Drive org-wide reliability strategy
• Own and build new detection & observability systems
• Tackle complex distributed systems challenges
• Safeguard critical infrastructure for financial customers

What Success Looks Like

• Issues caught and resolved before customer impact
• Reliability is measurable and continuously improving
• Teams self-serve observability with scalable tools
• Clear, proactive incident communication builds trust
• Reliability becomes a competitive advantage

See yourself at Twilio

Join the team as Twilio’s next Security Engineer, Security Automation on Twilio’s Information Security Team.

About the job

This position is needed to assist Twilio’s Information Security Team operate more efficiently by improving and automating our critical security workflows.

As a Software Engineer, Security Automation on this team, you will participate in all phases of the software development life cycle which includes requirements gathering with security teams, technical design, estimations, sprint planning, coding, testing, deployments and on-call support. You will own, operate and maintain automated workflows that support various security programs including but not limited to cloud security, product security, Governance, Risk & Compliance (GRC)  and enterprise security, employing Agile methodologies to continuously deliver value to our partners.

Responsibilities

In this role, you’ll:

• Develop and implement automated and AI-powered security solutions to protect Twilio's Cloud and Enterprise infrastructure, leveraging data orchestration frameworks and LLM-based approaches.
• Build workflows that integrate structured and unstructured data sources into orchestrated pipelines, enabling intelligent decision-making and risk reduction at scale.
• Design and prototype LLM-driven applications to automate security analysis, incident response, and governance tasks, while ensuring explainability and accuracy.
• Collaborate with cross-functional teams to identify security needs and deliver advanced AI-enabled solutions that address those needs effectively.
• Contribute significantly to defining our security automation and AI roadmap, balancing near-term and long-term business impact with technical feasibility and scalability.
• Own and maintain the operational health of automation and AI-driven systems, ensuring they continue to meet reliability and performance requirements (SLOs and KPIs).
• Support on-call operations for tools, pipelines, and AI models owned by the team.
• Document and share knowledge through clear technical documentation of processes, procedures, AI models, and orchestration systems.
• Stay up-to-date on emerging trends in security automation, data orchestration, and AI/LLMs—and apply them to Twilio’s security operations for continuous innovation.

Qualifications 

Not all applicants will have skills that match a job description exactly. Twilio values diverse experiences in other industries, and we encourage everyone who meets the required qualifications to apply. While having “desired” qualifications make for a strong candidate, we encourage applicants with alternative experiences to also apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!

Required:

• Minimum of five (5) years of experience as a software engineer developing internal tools and automating workflows at scale
• Proficiency in Python (or another scripting language) for development, testing, and automation of security and infrastructure workflows
• Hands-on experience applying AI/ML models, including LLMs, to automate complex business or security processes and build intelligent solutions
• Solid understanding of software security principles, secure coding practices, and security automation
• Experience with data orchestration frameworks (e.g., Airflow, Dagster, Prefect) to manage and scale automation pipelines
• Familiarity with infrastructure-as-code (Terraform), CI/CD systems (BuildKite or similar), and container orchestration platforms (Kubernetes, Docker)
• Strong problem-solving, communication, and collaboration skills, with the ability to iterate quickly on feedback and work across security and engineering teams

Desired:

• Experience with Security Orchestration, Automation, and Response (SOAR) technologies and practices, with a focus on scaling automated incident response
• Proven ability to design and implement security automation frameworks that enable rapid delivery of reliable, reusable, and scalable automated solutions
• Strong interest in or hands-on experience with building and applying AI/ML models (including LLMs) to automate complex workflows in cybersecurity, compliance, or infrastructure operations
• Ability to bridge AI/automation capabilities with security strategy, driving adoption of next-generation solutions across cloud and enterprise environments
• Passion for continuous innovation in leveraging orchestration, automation, and AI to solve real-world security challenges

Location

This role will be remote, and based in Ireland.

Travel

We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings.

What We Offer

There are many benefits to working at Twilio, including, in addition to competitive pay, things like generous time-off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.

See yourself at Twilio

Join the team as Twilio’s next Security Engineer, Security Automation on Twilio’s Information Security Team.

About the job

This position is needed to assist Twilio’s Information Security Team operate more efficiently by improving and automating our critical security workflows.

As a Software Engineer, Security Automation on this team, you will participate in all phases of the software development life cycle which includes requirements gathering with security teams, technical design, estimations, sprint planning, coding, testing, deployments and on-call support. You will own, operate and maintain automated workflows that support various security programs including but not limited to cloud security, product security, Governance, Risk & Compliance (GRC)  and enterprise security, employing Agile methodologies to continuously deliver value to our partners.

Responsibilities

In this role, you’ll:

• Develop and implement automated and AI-powered security solutions to protect Twilio's Cloud and Enterprise infrastructure, leveraging data orchestration frameworks and LLM-based approaches.
• Build workflows that integrate structured and unstructured data sources into orchestrated pipelines, enabling intelligent decision-making and risk reduction at scale.
• Design and prototype LLM-driven applications to automate security analysis, incident response, and governance tasks, while ensuring explainability and accuracy.
• Collaborate with cross-functional teams to identify security needs and deliver advanced AI-enabled solutions that address those needs effectively.
• Contribute significantly to defining our security automation and AI roadmap, balancing near-term and long-term business impact with technical feasibility and scalability.
• Own and maintain the operational health of automation and AI-driven systems, ensuring they continue to meet reliability and performance requirements (SLOs and KPIs).
• Support on-call operations for tools, pipelines, and AI models owned by the team.
• Document and share knowledge through clear technical documentation of processes, procedures, AI models, and orchestration systems.
• Stay up-to-date on emerging trends in security automation, data orchestration, and AI/LLMs—and apply them to Twilio’s security operations for continuous innovation.

Qualifications 

Not all applicants will have skills that match a job description exactly. Twilio values diverse experiences in other industries, and we encourage everyone who meets the required qualifications to apply. While having “desired” qualifications make for a strong candidate, we encourage applicants with alternative experiences to also apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!

Required:

• Minimum of five (5) years of experience as a software engineer developing internal tools and automating workflows at scale
• Proficiency in Python (or another scripting language) for development, testing, and automation of security and infrastructure workflows
• Hands-on experience applying AI/ML models, including LLMs, to automate complex business or security processes and build intelligent solutions
• Solid understanding of software security principles, secure coding practices, and security automation
• Experience with data orchestration frameworks (e.g., Airflow, Dagster, Prefect) to manage and scale automation pipelines
• Familiarity with infrastructure-as-code (Terraform), CI/CD systems (BuildKite or similar), and container orchestration platforms (Kubernetes, Docker)
• Strong problem-solving, communication, and collaboration skills, with the ability to iterate quickly on feedback and work across security and engineering teams

Desired:

• Experience with Security Orchestration, Automation, and Response (SOAR) technologies and practices, with a focus on scaling automated incident response
• Proven ability to design and implement security automation frameworks that enable rapid delivery of reliable, reusable, and scalable automated solutions
• Strong interest in or hands-on experience with building and applying AI/ML models (including LLMs) to automate complex workflows in cybersecurity, compliance, or infrastructure operations
• Ability to bridge AI/automation capabilities with security strategy, driving adoption of next-generation solutions across cloud and enterprise environments
• Passion for continuous innovation in leveraging orchestration, automation, and AI to solve real-world security challenges

Location

This role will be remote, and based in the UK.

Travel

We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings.

What We Offer

There are many benefits to working at Twilio, including, in addition to competitive pay, things like generous time-off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.

Key Responsibilities   

• Lead large cross-team security initiatives from planning to delivery;  
• Break down complex security programs into phases, milestones, dependencies, and execution plans; 
• Coordinate execution across multiple engineering and platform teams, ensuring alignment and momentum;  
• Translate product requirements into clear, actionable workstreams for engineering teams; 
• Build and maintain project plans, documentation, decision logs, and technical context; 
• Run regular project syncs and reviews - track progress, identify blockers early, and drive mitigation; 
• Own timeline tracking and delivery forecasting - proactively highlight risks and trade-offs; 
• Partner closely with Product Managers to orchestrate execution across multiple teams; 
• Improve delivery transparency through clear status reporting, milestone tracking, and stakeholder communication; 
• Ensure cross-team dependencies are surfaced early and resolved before becoming blockers.  

What We Expect 

• Strong technical awareness in security and Cloud environments, with solid understanding of:  
• Cloud and infrastructure security principles  
• Kubernetes and container security  
• IAM Fundamentals 
• Cloud networking concepts (VPC, Security Groups)  
• Security tooling and platforms  
• Experience driving execution in complex, multi-team technical environments; 
• Strong project decomposition and execution management skills; 
• Ability to coordinate and run structured cross-functional processes across engineering and product teams; 
• Strong communication skills: concise status reporting, clear risk communication, and stakeholder alignment; 
• Experience working closely with both product managers and engineering managers in platform or infrastructure-heavy environments.  

Nice to Have 

• Experience working with Cloud platforms, distributed systems, or AI/ML infrastructure environments; 
• Experience working at a Cloud Service Provider; 
• Familiarity with advanced security domains such as confidential computing or federated computing; 
• Background in high-scale infrastructure or platform organizations.  

Success In This Role 

• Security initiatives are delivered predictably, with clear execution plans and realistic timelines; 
• Cross-team alignment is strong across product and engineering for complex security programs; 
• Risks and dependencies are identified early and actively managed; 
• Execution of security priorities becomes smoother, with reduced friction across teams; 
• Stakeholders have clear visibility into progress, risks, and next steps.  

About Nebius

Nebius AI is an AI cloud platform with one of the largest GPU capacities in Europe. Launched in November 2023, the Nebius AI platform provides high-end, training-optimized infrastructure for AI practitioners. As an NVIDIA preferred cloud service provider, Nebius AI offers a variety of NVIDIA GPUs for training and inference, as well as a set of tools for efficient multi-node training. 

Nebius AI owns a data center in Finland, built from the ground up by the company’s R&D team and showcasing our commitment to sustainability. The data center is home to ISEG, the most powerful commercially available supercomputer in Europe and the 16th most powerful globally (Top 500 list, November 2023).  

Nebius’s headquarters are in Amsterdam, Netherlands, with teams working out of R&D hubs across Europe and the Middle East. 

Nebius AI is built with the talent of more than 500 highly skilled engineers with a proven track record in developing sophisticated cloud and ML solutions and designing cutting-edge hardware. This allows all the layers of the Nebius AI cloud – from hardware to UI – to be built in-house, distictly differentiating Nebius AI from the majority of specialized clouds: Nebius customers get a true hyperscaler-cloud experience tailored for AI practitioners. We’re growing and expanding our products every day. 

If you’re up to the challenge and are excited about AI and ML as much as we are, join us!

The role

We’re looking for a Backend Engineer to contribute to the development of our hyperscaler platform.

Your responsibilities will include:

Develop fault-tolerant, reliable cloud services: cloud infrastructure, managed databases, managed Kubernetes, billing, monitoring systems, ML service and more.

We expect you to have: 

• 5+ years of professional software engineering experience;
• Knowledge of C++ programming language;
• Knowledge of Python, Java, and Go is a plus;
• Ability to write reliable code and dig into complex problems;
• Teamwork-oriented approach;
• Fluency in English.

Nice to have:

Experience designing high-load and scaling services.

We conduct coding interviews as part of the process.

• Write and maintain UI copy in Nebius Console that improves and streamlines the user experience, ensuring consistency and alignment with product documentation.
• Provide alternative UI copy options based on the proposed design solutions.
• Collaborate closely with product managers, designers, and engineers on product initiatives.
• Develop and maintain voice & tone guidelines; define and scale content patterns within the design system.
• Simplify complex technical scenarios into clear, actionable interface language.
• Conduct content audits of the existing interfaces and identify areas for improvement.
• Actively participate in the life and processes of the Product Design Team.

• 5+ years of experience in UX writing / content design.
• Strong product thinking and the ability to approach design as a system of interconnected user scenarios.
• Excellent written and spoken English.
• Familiarity with cloud computing concepts (virtual machines, containers, Kubernetes, storage, networking, etc.) and ML/AI concepts (training, inference, fine-tuning, etc.).
• Proficiency in Figma.
• A portfolio featuring real interface cases (before/after examples and clear explanation of decision logic).
• Solid understanding of core UX principles: user flows, edge cases, states, and system feedback.

• Experience in technical writing.
• Experience using AI-powered plugins in Figma or other tools to support content creation workflows.
• Review UI texts directly in the codebase and occasionally update or fix copy within the code when necessary.

The role

We’re looking for a Software Engineer with strong C++ expertise to join the team building and operating Nebius Data Platform — a distributed storage and a processing platform that acts as the company’s “source of truth” and the backbone of many internal (and some external) products.

Nebius Data Platform is a single multi-tenant ecosystem based on YTsaurus — instead of running separate HDFS/Kafka/HBase-style systems, we provide storage, compute, and analytics capabilities inside one platform.

Built on top of the open-source YTsaurus ecosystem, we run and extend our own Nebius distribution and develop significant in-house functionality (core and platform-level). We can design, implement, and roll out features end-to-end on our clusters without waiting for upstream approvals and contribute upstream when it makes sense.

At scale today, this includes~500 servers, ~20k CPU cores and ~10 PB of compressed data in our largest production cluster, supporting workloads ranging from business-critical pipelines and financial transactions to large-scale ML/LLM training datasets and compute.

What’s inside the platform

You’ll work on a system that includes (and ties together):

• Distributed Storage (Cypress): transactional semantics, tiered storage, erasure coding, replication, and strong reliability expectations.
• Compute & ETL: a cluster-wide job scheduler (tens of thousands of cores), MapReduce, YQL for SQL-like data processing, and SPYT (Spark over YTsaurus) for modern data engineering.
• Interactive analytics (CHYT): ClickHouse® instances spun up directly on compute nodes for fast SQL over data in-place.
• Dynamic Tables: low-latency NoSQL KV with distributed ACID transactions for OLTP-style workloads and feature stores.
• Orchestracto: workflow orchestration deeply integrated with the platform (Airflow-like, but platform-native).

What you’ll do

We’re looking for engineers who combine strong systems skills with product sense: understanding who uses the platform, why certain capabilities matter, and making pragmatic trade-offs to maximize impact. On our team, engineering work is expected to be connected to real users and outcomes — you’ll regularly align with internal stakeholders, clarify requirements, and help drive prioritization.

In this role, you will:

• Design and implement new functionality in YTsaurus core (C++) with production reliability in mind.
• Build and evolve platform-level capabilities: platform architecture and operating model—multi-cluster growth, shared primitives, and a consistent experience that scales with new teams and use cases.
• Improve end-to-end platform experience for internal (and external-facing) users: APIs, guardrails, debugging workflows, and automation.
• Own production quality: incident response / on-call rotation, root cause analysis, and turning learnings into durable fixes.

Example projects

• Roll out sharded YTsaurus masters (incl. Kubernetes operator support) and build automatic balancing of metadata across master cells (consensus groups) to remove control-plane bottlenecks and unlock 10–100x cluster growth.
• Make CHYT interactive SQL faster and more predictable at high load via performance work like data-skipping / min-max-style indexes and improved execution introspection.
• Turn Orchestracto into a platform product by defining the building blocks, developer experience, and governance for how teams create and share workflows.
• Scale and harden Parquet-on-S3 for native YTsaurus workloads by tackling replication/movement, consistent lifecycle semantics, and master-server metadata optimizations for performance and reliability.
• Design and ship complete, trustworthy audit trails for data changes (who/what/when) across heterogeneous storage and compute paths.

Tech stack

• Core: modern C++ (C++20, async + multithreaded primitives)
• Services & tooling: Go and Python (microservices, utilities, integration tests)

What we expect

• 5+ years of software engineering experience.
• Strong C++ skills (you’ll write core code).
• Working knowledge of Python and/or Go (you don’t have to be expert, but should be comfortable navigating them).
• Experience developing and/or operating high-load, distributed services.
• Production mindset: ability to use SSH, read logs/metrics/traces, and debug distributed systems behavior.
• Solid CS fundamentals: algorithms, data structures, concurrency basics.

Nice to have

• Experience with Big Data systems (YTsaurus/Hadoop/Spark/ClickHouse/Kafka-like ecosystems).
• Experience with multi-tenant platforms, schedulers, resource isolation, quotas, and reliability engineering.
• Strong performance engineering skills (profiling, lock contention, latency/throughput tradeoffs).

We conduct coding interviews as part of the process.

The team

Customer experience at Nebius GPU AI Cloud involves tackling customers’ challenges and directly impacting their success by solving real-world AI and ML problems at massive GPU cloud scale. You’ll not only resolve issues, but play a key role in shaping clients’ business success by optimizing their AI solutions. Working with advanced GPUs such as H200, B200 and GB200, as well as modern ML frameworks, you’ll influence the development of the Nebius AI Cloud and gain experience at the intersection of infrastructure and AI. With minimal bureaucracy, you’ll have the freedom to innovate, take ownership and drive change. Opportunities for growth are abundant in this vibrant and supportive professional community.

The role

We are seeking a highly skilled and customer-focused leader to join our team as a Cloud Solutions Architect Lead. As a team leader, you will play a pivotal role in customer success across EU region, both managing the efforts of Cloud Solutions Architects team (technical and process excellence, talent development) and building processes alongside your stakeholders. Player-coach mentality and proven track record of managing high expertise teams is a must. 

You’re welcome to work from our office in Amsterdam or remotely from any EU country.

Your responsibilities will include: 

• Lead and mentor a team of Solutions Architects, fostering a culture of technical excellence, customer empathy, and collaborative execution.
• Oversee and participate in technical engagements including PoCs, workshops, architecture reviews, and trainings.
• Drive consistency and quality across infrastructure design, IaC practices, technical documentation, and customer enablement content.
• Collaborate closely with Product and Development teams, representing customer needs and helping shape the roadmap.
• Guide customers in optimizing ML/AI/HPC pipelines for performance, scalability, and cost-efficiency on Nebius  cloud infrastructure.
• Build visibility and ownership culture amongst Solutions Architects.

We expect you to have: 

• 5+ years of experience in a technical role (Solutions Architect, DevOps Engineer, ML Engineer, or similar) with a focus on cloud-native systems and distributed computing.
• 2+ years of experience leading or mentoring customer facing engineering teams.
• Deep hands-on experience with Infrastructure as Code (Terraform, Ansible), Kubernetes, and cloud automation.
• Strong communication and stakeholder management skills across both technical and non-technical audiences.
• Passion for developing scalable, reliable cloud architectures and driving customer success.

It will be an added bonus if you have: 

• Experience with HPC or ML orchestration frameworks (e.g., Slurm, Kubeflow, Ray).
• Strong coding skills in Python and experience with GPU computing environments for ML/AI workloads.
• Proficient in GPU stack components (e.g., CUDA, cuDNN) and cloud-native patterns for ML training/inference.
• Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX).
• Understanding of cloud-based ML tools and offerings from NVIDIA, AWS, Azure, or Google Cloud.
• Experience participating in or leading technical contributions to conferences or open-source communities. 

The role

We seek an experienced Specialist Solutions Architect to support AI-focused customers leveraging Nebius services. In this role, you will be a trusted advisor, collaborating with clients to design scalable AI solutions, resolve technical challenges and manage large-scale AI deployments involving hundreds to thousands of GPUs.

You’re welcome to work on-site in Amsterdam or remotely from any other EU country.

Your responsibilities will include:

• Designing customer-centric solutions that maximize business value and align with strategic goals.
• Building and maintaining long-term relationships to foster trust and ensure customer satisfaction.
• Delivering technical presentations, producing whitepapers, creating manuals and hosting webinars for audiences with varying technical expertise.
• Collaborating with engineering and product teams to effectively prioritize and relay customer feedback.

We expect you to have:

• 3+ years of experience with cloud technologies in MLOps engineering, Machine Learning engineering or similar roles.
• Strong understanding of ML ecosystems, including models, use cases and tooling.
• Proven experience in setting up and optimizing distributed training pipelines across multi-node and multi-GPU environments.
• Hands-on knowledge of frameworks like PyTorch or JAX.
• Excellent verbal and written communication skills.

It will be an added bonus if you have:

• Expertise in deploying inference infrastructure for production workloads.
• Ability to transition ML pipelines from POC to scalable production systems.

Preferred tooling:

• Programming Languages – Python, Go, Java, C++
• Orchestration – Kubernetes (K8s), Slurm
• DevOps Tools – Git, Docker, Helm
• Infrastructure as Code (IaC) – Terraform
• ML Frameworks and Libraries – PyTorch, TensorFlow, JAX, HuggingFace, Scikit-learn

The role 

The Data Engineering team is responsible for building and maintaining robust data infrastructure that powers analytics, and business intelligence across Nebius. We design and implement scalable data pipelines, optimize data storage and processing, and enable data-driven decision making across the organization. The team works closely with product teams and business stakeholders to ensure alignment with company goals.We are looking for a Data Engineer to design, build, and maintain our data infrastructure and pipelines. You will work on processing large-scale datasets, optimizing data workflows, and enabling analytics capabilities that support our rapidly growing cloud platform.

Your responsibilities: 

• Design, develop, and maintain scalable data pipelines.
• Build and optimize data infrastructure.
• Implement data quality monitoring and validation frameworks.
• Optimize data storage, processing, and query performance for large-scale datasets.
• Design and implement data models for analytics and reporting use cases.
• Develop tools and automation to improve data engineering workflows and productivity.
• Ensure data governance, security, and compliance standards are met.
• Participate in on-call rotation to support production data systems.

Must-haves: 

• 3+ years of experience in data engineering or related roles.
• Experience building and maintaining data pipelines using orchestration tools (e.g., Airflow, Prefect, Dagster).
• Strong proficiency in SQL and solid programming skills in Python.
• Experience with distributed data processing frameworks (e.g., Apache Spark, or similar).
• Knowledge of data modeling principles and best practices.
• Understanding of data architectures and storage systems.

Nice-to-haves: 

• Experience with real-time data streaming platforms.
• Familiarity with Infrastructure as Code tools (Terraform, etc).
• Experience with containerization (Docker) and Kubernetes.
• Knowledge of data governance and privacy frameworks (GDPR, SOC2).
• Knowledge of data quality and observability tools (Great Expectations, etc.).

We conduct coding interviews as part of the process.

Nebius Managed Kubernetes (mk8s) mission is to grow the Nebius cloud platform by providing a Kubernetes-native way to run AI systems with high efficiency and low operational overhead.
With a single click, it provides a Kubernetes cluster on top of Nebius services for compute (VMs) and networking.
In 2026, the service is scaling 10× and is expected to manage customer workloads across tens of thousands of GPU servers in more than 10 data centers.

You will lead the mk8s Core team, one of three mk8s teams. The Core team owns the API, the core of the service control plane, cluster autoscaling, platform integrations, and running k8s add-ons.

At Nebius, team leads are hands-on. We expect you to be a senior or staff engineer now (or earlier in your career). You will start as an individual contributor to gain context, then take on managerial responsibilities.

In this position, you will be responsible to:

• Lead by example. Set the quality bar by spending a significant portion of your time on IC work: writing and reviewing code, leading projects, and participating in on-call rotation, incident mitigation, and post-incident analysis.
• Manage 4–8 mid-to-senior engineers. Provide context, coach, and give regular feedback.
• Maintain the technical vision for your area of responsibility.
• Collaborate with the Product Manager and Service Owner to shape product vision and plans.

Examples of outcomes you could drive as a Team Lead

• Optimize the service control plane to create and manage 20K GPU nodes in a single Kubernetes cluster, enabling a major contract for the company.
• Integrate cluster autoscaling approaches (e.g., Karpenter) to improve resource utilization and support seamless auto-upgrades.
• Provide a Kubernetes-native way to use local disks to reduce disk I/O bottlenecks for AI training and inference, improving efficiency.
• Deliver managed Layer 7 load balancers to reduce operational overhead for customers.

What you will bring to the table:

• 8+ years of professional software engineering or management experience
• Excellent knowledge of Golang, or you are ready to quickly switch to this programming language
• Expertise with
• Multi-month technical projects
• Tech leading engineers
• Owning multi-month technical projects.

It would be an added bonus if you had:

• Experience with Team management, Kubernetes administration, Developing Kubernetes controllers

The role

We are seeking a highly skilled and customer-focused professional to join our team as a Solutions Architect specializing in Cloud infrastructure and MLOps. As a Cloud Solutions Architect, you will play a pivotal role in designing and implementing cutting-edge solutions for our clients, leveraging cloud technologies for ML/AI teams and becoming a trusted technical advisor for building their pipelines.

You’re welcome to work from the United Kingdom.

Your responsibilities will include: 

• Act as a trusted advisor to our clients, providing technical expertise and guidance throughout the engagement. Conduct PoC, workshops, presentations, and training sessions to educate clients on GPU cloud technologies and best practices.
• Collaborate with clients to understand their business requirements and develop solution architecture that align with their needs: design and document Infrastructure as code solutions, documentation and technical how-tos in collaboration with support engineers and technical writers.
• Help customers to optimize pipeline performance and scalability to ensure efficient utilization of cloud resources and services powered by Nebius AI.
• Act as a single point of expertise of customer scenarios for product, technical support, marketing teams.
• Assist to Marketing department efforts during events (Hackathons, conferences, workshops, webinars, etc.)

We expect you to have: 

• 5+ years of experience as a cloud solutions architect, system/network engineer, developer or a similar technical role with a focus on cloud computing
• Strong hands-on experience with IaC and configuration management tools (preferably Terraform/Ansible), Kubernetes, skills of writing code in Python
• Solid understanding of GPU computing practices for ML training and inference workloads, GPU software stack components, including drivers, libraries (e.g. CUDA, OpenCL)
• Excellent communication skills
• Customer-centric mindset

It will be an added bonus if you have: 

• Hands-on experience with HPC/ML orchestration frameworks (e.g. Slurm, Kubeflow)
• Hands-on experience with deep learning frameworks (e.g. TensorFlow, PyTorch)
• Solid understanding of cloud ML tools landscape from industry leaders (NVIDIA, AWS, Azure, Google) 

The role

We are looking for a Customer Engineer to support key and strategic Nebius GPU Cloud services customers. In this role, you will be a trusted technical advisor, helping clients design, deploy, and scale AI solutions while managing large-scale GPU workloads involving hundreds to thousands of GPUs. You will also collaborate with sales and product teams to drive growth and enhance customer satisfaction.

You’re welcome to work remotely from Europe.

Your responsibilities will include:

• Serve as the primary technical point of contact for troubleshooting and resolving complex AI/ML issues.
• Guide customers in optimizing GPU performance for ML training and inference workloads, ensuring seamless integration and scalability.
• Partner with the sales team to identify new opportunities, promote the latest products, and deliver technical presentations.
• Act as a bridge to product teams, providing customer feedback, relaying feature requests, and ensuring alignment with customer requirements.
• Engage with internal and external stakeholders, negotiate solutions, and effectively drive alignment to address customer challenges.

We expect you to have:

• Experience: 5+ years in roles like Solutions Architect, Technical Account Manager, or Customer Engineer, with hands-on experience in cloud services and AI/ML workloads.
• Proficiency in Infrastructure as Code (IaC) tools like Terraform and Ansible.
• Experience with Kubernetes and Python programming.
• Solid understanding of GPU computing, including ML training, inference workloads, and GPU stacks (e.g., CUDA, OpenCL).
• Customer-centric approach with a proven ability to build trust and foster long-term relationships.
• Strong ability to explain technical concepts to technical and non-technical audiences.

It will be an added bonus if you have:

• Hands-on experience with HPC/ML orchestration frameworks (e.g., Slurm, Kubeflow).
• Experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
• Familiarity with ML tools from NVIDIA, AWS, Azure, and Google Cloud providers.
• Strong project management skills, with the ability to prioritize tasks and deliver on deadlines.
• Proven experience mentoring technical teams and driving team growth.
• Expertise in stakeholder negotiation to support problem resolution and ensure seamless collaboration.

• Serverless AI has clear product-market fit with measurable activation and retention metrics improving quarter over quarter.
• Multi-node jobs and autoscaling endpoints are shipped and adopted by customers running production workloads.
• Cold start time is reduced from 1-3 minutes to under 60 seconds for common workloads through a combination of product and infrastructure improvements you drove.
• Developer experience (CLI, docs, error messages, onboarding flow) sets the standard that developers expect from a next-generation AI cloud.
• At least 3 product decisions you made are directly attributable to customer conversations or data analysis you conducted.

• Co-own the Serverless AI product roadmap — Jobs, Endpoints, and DevPods — taking primary ownership of specific product areas while collaborating closely with the other PM on shared priorities and cross-cutting decisions.
• Write detailed, technically precise PRDs that engineering teams can execute against. Our PRDs specify CLI syntax, API contracts, state machines, and billing models — not abstract feature descriptions.
• Make build/buy/defer decisions on capabilities like autoscaling, multi-node orchestration, HTTPS termination, secret injection, and health checking based on customer signal and strategic priorities.

• Understand the full workload lifecycle: container image pull → VM provisioning → GPU attachment → workload execution → cleanup — well enough to identify bottlenecks and propose solutions.
• Evaluate technical trade-offs in areas like container cold start optimization (image caching, snapshot restore, warm pools), GPU scheduling and bin-packing, and storage mount performance.
• Work directly with engineers on architecture decisions for distributed training support, endpoint autoscaling policies, and fault tolerance mechanisms.
• Stay current on the fast-moving serverless GPU infrastructure space — new inference frameworks (vLLM, TensorRT-LLM, SGLang), container runtimes, orchestration approaches — and translate trends into product direction.

• Run customer discovery and feedback sessions with ML engineers and platform teams at AI startups and enterprises. Turn qualitative insight into specific product actions.
• Analyze usage data, activation funnels, and churn patterns to identify where users get stuck and what features drive retention.
• Track market dynamics, emerging technologies, and industry trends to inform product strategy and ensure Nebius stays ahead of where the market is heading.
• Define and iterate on pricing, packaging, and tier strategy for Serverless AI.

• Own the technical content strategy: quickstart guides, tutorials, reference architectures, and example workloads that reduce time-to-first-job.
• Partner with marketing on developer-focused campaigns, webinars, and conference presence.
• Work with Solution Architects and Sales to qualify serverless-fit opportunities and support technical evaluations.

• You have built, shipped, and iterated on infrastructure or platform products used by developers or ML engineers. Not consumer apps. Not dashboards. Infrastructure.
• You understand containers at a practical level — Docker, image registries, container runtimes, resource limits, networking. You've debugged why a container won't start, why GPU isn't visible inside it, or why a mount isn't working.
• You have working knowledge of GPU computing for AI/ML: what GPU types exist and when to use them, how training and inference workloads differ in resource requirements, what vLLM / TensorRT-LLM / Triton are and why they matter.
• You can read a CLI reference and know if it's well-designed. You've shaped developer-facing APIs, CLIs, or SDKs.
• You have run real customer discovery — not surveys, but technical conversations with engineers where you learned something that changed your product direction.
• You have 3+ years of product management experience in cloud infrastructure, AI/ML platforms, or developer tools.

• Ability to whiteboard a workload lifecycle (submit → schedule → provision → execute → cleanup) and identify failure modes at each step.
• Understanding of autoscaling trade-offs: scale-to-zero vs. warm pools, scaling metrics (queue depth, latency, utilization), cold start implications.
• Familiarity with inference serving concepts: batching, model loading, quantization, KV-cache management, multi-model serving.
• Understanding of distributed training concepts: data parallelism, model parallelism, communication overhead, checkpointing.
• Ability to reason about pricing models: per-second vs. per-request vs. per-token, and how pricing interacts with product architecture.

• Experience at a serverless or GPU cloud company.
• Hands-on ML engineering background — you've trained models, deployed inference endpoints, or built ML pipelines yourself.
• Experience with Kubernetes for ML workloads (Kubeflow, KServe, Ray Serve) and understanding of why many ML teams want to avoid it.
• Prior experience building a product from early stage to scale in a fast-growing market.
• Background in systems engineering, distributed systems, or site reliability engineering.

• You are more comfortable in a terminal than in a slide deck.
• You form strong opinions based on data and direct customer signal, and you update them when evidence changes.
• You are energized by building at pace — small team, fast-evolving product, big opportunity.
• You care about developer experience at the level of error messages, CLI flag naming, and documentation quality.
• You'd rather ship a smaller thing that works perfectly than a bigger thing that's mediocre.

About Nebius

Nebius AI is an AI cloud platform with one of the largest GPU capacities in Europe. Launched in November 2023, the Nebius AI platform provides high-end, training-optimized infrastructure for AI practitioners. As an NVIDIA preferred cloud service provider, Nebius AI offers a variety of NVIDIA GPUs for training and inference, as well as a set of tools for efficient multi-node training. 

Nebius AI owns a data center in Finland, built from the ground up by the company’s R&D team and showcasing our commitment to sustainability. The data center is home to ISEG, the most powerful commercially available supercomputer in Europe and the 16th most powerful globally (Top 500 list, November 2023).  

Nebius’s headquarters are in Amsterdam, Netherlands, with teams working out of R&D hubs across Europe and the Middle East. 

Nebius AI is built with the talent of more than 500 highly skilled engineers with a proven track record in developing sophisticated cloud and ML solutions and designing cutting-edge hardware. This allows all the layers of the Nebius AI cloud – from hardware to UI – to be built in-house, distictly differentiating Nebius AI from the majority of specialized clouds: Nebius customers get a true hyperscaler-cloud experience tailored for AI practitioners. We’re growing and expanding our products every day. 

If you’re up to the challenge and are excited about AI and ML as much as we are, join us!

The role

We are seeking a customer-obsessed Solutions Architect to lead technical engagement with Nebius customers across Europe. This role is focused on presales excellence, strong technical storytelling, and driving adoption of Nebius AI Cloud across a wide range of industry segments.

As a Solutions Architect, you will act as a trusted technical partner to customers, helping them understand, evaluate, and adopt Nebius for their AI/ML and high-performance computing workloads. You will combine deep technical expertise with strong communication skills to clearly articulate Nebius’ value proposition and differentiate our platform in a competitive market.

You’re welcome to work remotely from Europe.

Your responsibilities will include:

• Own end-to-end technical presales engagements, from discovery through solution design, PoC execution, and production readiness
• Serve as a trusted technical advisor to customer stakeholders, including CTOs, Heads of AI/ML, and platform engineering teams
• Deliver compelling technical presentations, demos, and workshops that clearly communicate the value of Nebius across different customer segments
• Execute demos and PoCs to demonstrate performance, scalability, and cost efficiency of Nebius solutions
• Translate customer requirements into scalable, production-ready architectures and best practices
• Collaborate closely with Sales, Product, and Engineering to align customer needs with Nebius capabilities and roadmap
• Act as a technical advocate for customers internally, ensuring feedback is incorporated into product and go-to-market strategy
• Support regional go-to-market efforts, including events, meetups, webinars, and technical content creation
• Contribute to building repeatable technical playbooks and assets for the European market

We expect you to have:

• 2–5+ years of experience in technical roles such as Solutions Architect, Cloud Architect, Sales Engineer, or similar, with strong customer-facing exposure
• Proven experience in presales or customer-facing technical roles, including discovery, solution design, and PoC execution
• Strong ability to deliver technical pitches and clearly explain complex infrastructure and AI/ML concepts to both technical and business audiences
• Experience positioning cloud or infrastructure solutions and articulating value propositions in competitive environments
• Solid understanding of ML/AI workloads, including training and inference, and the underlying infrastructure requirements
• Experience with cloud platforms, Kubernetes, and distributed systems
• Hands-on experience with Infrastructure as Code (e.g., Terraform) and scripting/programming (Python preferred)
• Strong communication and storytelling skills, with the ability to adapt messaging across different customer segments
• Deep understanding of the European market, including customer expectations, buying behaviors, and local ecosystem
• Fluency in English plus another language preferred (both written and spoken), with the ability to engage confidently with local customers and stakeholders
• A highly customer-centric mindset, with the ability to balance technical depth and business value

It will be an added bonus if you have:

• Experience with GPU-accelerated workloads and AI infrastructure (NVIDIA ecosystem, CUDA, etc.)
• Hands-on experience with MLOps tools and frameworks (Kubeflow, MLflow, etc.)
• Familiarity with HPC environments and schedulers (e.g., Slurm)
• Experience contributing to regional go-to-market or developer/community initiatives

Token Factory is a part of  Nebius Cloud, one of the world’s largest GPU clouds, running tens of thousands of GPUs. We are building an inference platform that makes every kind of foundation model — text, vision, audio, and emerging multimodal architectures — fast, reliable, and effortless to deploy at massive scale. To deliver on that promise, we need an engineer who can make the platform behave flawlessly under extreme load and recover gracefully when the unexpected happens.

In this role you will own the reliability, performance, and observability of the entire inference stack. Your day starts with designing and refining telemetry pipelines — metrics, logs, and traces that turn hundreds of terabytes of signal into clear, actionable insight. From there you might tune Kubernetes autoscalers to squeeze more efficiency out of GPUs, craft Terraform modules that bake resilience into every new cluster, or harden our request-routing and retry logic so even transient failures go unnoticed by users. When incidents do arise, you’ll rely on the automation and runbooks you helped create to detect, isolate, and remediate problems in minutes, then drive the post-mortem culture that prevents recurrence. All of this effort points toward a single goal: scaling the platform smoothly while hitting aggressive cost and reliability targets.

Success in the role calls for deep fluency with Kubernetes, Prometheus, Grafana, Terraform, and the craft of infrastructure-as-code. You script comfortably in Python or Bash, understand the nuances of alert design and SLOs for high-throughput APIs, and have spent enough time in production to know how distributed back-ends fail in the real world. Experience shepherding GPU-heavy workloads — whether with vLLM, Triton, Ray, or another accelerator stack — will serve you well, as will a background in MLOps or model-hosting platforms. Above all, you care about building self-healing systems, thrive on debugging performance from kernel to application layer, and enjoy collaborating with software engineers to turn reliability into a feature users never have to think about.

If the idea of safeguarding the infrastructure that powers tomorrow’s multimodal AI energizes you, we’d love to hear your story.

The role

Nebius seeks a Key Customers Solutions Architect to support key and strategic Nebius GPU Cloud services customers. In this role, you will be a trusted technical advisor, helping clients design, deploy, and scale AI solutions while managing large-scale GPU workloads involving hundreds to thousands of GPUs. You will also collaborate with sales and product teams to drive growth and enhance customer satisfaction.

You’re welcome to work remotely from Europe.

Your responsibilities will include: 

• Serve as the primary technical point of contact, troubleshooting and resolving complex AI/ML.
• Guide customers in optimizing GPU performance for ML training and inference workloads, ensuring seamless integration and scalability.
• Partner with the sales team to identify new opportunities, promote the latest products, and deliver technical presentations.
• Act as a bridge to product teams, providing customer feedback, relaying feature requests, and ensuring alignment with customer requirements.
• Engage with internal and external stakeholders, negotiate solutions, and effectively drive alignment to address customer challenges.

We expect you to have:

• Experience: 5 - 10 + years in roles like Cloud Solutions Architect, Technical Account Manager, or Customer Engineer, with hands-on experience in cloud services and AI/ML workloads.
• Proficiency in Infrastructure as Code (IaC) tools like Terraform and Ansible.
• Experience with Kubernetes and Python programming.
• Solid understanding of GPU computing, including ML training, inference workloads, and GPU stacks (e.g., CUDA, OpenCL).
• Customer-centric approach with a proven ability to build trust and foster long-term relationships.
• Strong ability to explain technical concepts to technical and non-technical audiences.

It will be an added bonus if you have:

• Hands-on experience with HPC/ML orchestration frameworks (e.g., Slurm, Kubeflow).
• Experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
• Familiarity with ML tools from NVIDIA, AWS, Azure, and Google Cloud providers.
• Strong project management skills, with the ability to prioritize tasks and deliver on deadlines.
• Proven experience mentoring technical teams and driving team growth.
• Expertise in stakeholder negotiation to support problem resolution and ensure seamless collaboration.

Role & Team

Our engineering team is growing! We are looking for multiple senior full stack engineers to join our web product team(s) and help us scale our product suite. 

As a Senior Software Engineer at Overstory, you will have a direct impact on our mission by building new capabilities and features that in turn enable utility companies to more effectively manage risks associated with climate change, wildfires and storms. We will also look to you to effectively partner with product, design and tech leads on key initiatives and mentor other engineers from time to time. 

Time zone requirement: Europe (GMT/WET, CET, EET) and Eastern North America (NST, AST, EST)

What You'll Do

Over the next 6-12 months you will contribute to:

• Performance & scalability: ensuring that our product can handle 3x year-over-year growth
• Velocity: accelerating time to value of new product capabilities
• Leverage: reducing the amount of manual work required to ingest vegetation analysis into our customer facing applications

Skills & Experience

• Proven experience of full stack development across the following (or similar) technologies: *Python/FastAPI, React/Typescript, Postgres DB, data pipelines; (*Python experience a core requirement)
• Recent experience working in a build it, run it environment (GCP, cloud run, grafana, k8s) - or similar
• Experience working in a high growth scaleup environment across distributed, remote teams 
• Deeply committed to tackling the climate crisis
• Possess a product mindset; deep understanding of leveraging technology to directly impact business outcomes
• Proven ability to design and implement scalable and resilient systems
• Excellent written and verbal communication skills; ability to effectively collaborate in a cross-functional team environment
• Committed to ongoing education, perpetual learning, mentorship; interested in evolving technologies and industry trends

Nice To Have

• Experience working with maps/imagery/geospatial domains  
• Experience working on globally distributed teams

Note: We believe that all people are capable of great things. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description.

What We Offer

• Competitive, location-specific compensation and benefits
• Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around
• Home office stipend, coworking and ongoing education budgets 
• A company culture that genuinely embodies each of our core values
• To be part of truly mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve our climate crisis

Role & Team

We’re looking for a Director of Platform & Infrastructure to own and evolve our core engineering foundations. Reporting to our VP of Product Engineering, this role will lead SRE, MLOps, and Platform teams with a mandate to create leverage across the entire organization.

As a scaling startup, we’re evolving from early-stage infrastructure to a more mature, reliable platform that can support rapid product development and growing customer demand. This role is critical in helping us make that transition — building systems, standards, and teams that enable speed today while laying the foundation for long-term scale.

Partnering closely with product, data, and application engineering teams, you will set the technical vision, define best practices, and ensure our infrastructure enables teams to move fast with confidence.

This is a highly cross-functional leadership role for someone who combines deep technical judgment with a systems mindset, strong people leadership, and a passion for building platforms that empower others.

Time zone requirement: Europe (GMT/WET, CET, EET) and Eastern North America (NST, AST, EST)

What You'll Do 

• Own the platform strategy across Platform, MLOps, and SRE, aligning it with company and product goals
• Grow senior ICs (and eventually manages) across multiple teams, fostering strong technical leadership and healthy team cultures
• Define and evolve our platform vision, including developer experience, internal tooling, CI/CD, infrastructure, observability, and reliability standards
• Oversee MLOps systems that support model development, training, deployment, monitoring, and governance in production
• Partner cross-functionally with Product, ML, Data, Security, and Compliance to ensure the platform meets current and future needs
• Balance speed and stability, making thoughtful tradeoffs between innovation, cost, reliability, and operational excellence
• Set metrics and accountability for platform performance, reliability, and developer productivity

Skills & Experience

• 10+ years experience leading platform, infrastructure, or reliability teams in a scaling startup environment, including navigating ambiguity, rapid growth, and the transition from early-stage systems to more mature, repeatable platforms
• Strong understanding of cloud-native infrastructure (GCP strongly preferred), Kubernetes, CI/CD, and modern DevOps practices
• Experience supporting machine learning systems in production, including model deployment, monitoring, and lifecycle management
• A track record of building reliable, scalable systems used by fast-moving product teams
• Excellent people leadership skills — you know how to coach managers, grow talent, and build inclusive, high-performing teams
• Strong communication skills and the ability to influence across org boundaries
• Experience in data- or ML-heavy products

Nice To Have

• Experience with geospatial data, image processing or mapping technology 

Note: We believe that all people are capable of great things. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description.

What We Offer

• Competitive, location-specific compensation and benefits.  
• Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around
• Home office stipend, coworking and ongoing education budgets 
• A company culture that genuinely embodies each of our core values
• To be part of truly mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve our climate crisis

Role & Team

As a Staff Engineer, you will work across multiple teams to evolve a suite of web and internal tools that enable utility companies to more effectively manage risks associated with climate change and wildfires.

We are seeking improvement in the following areas:

• Performance & Scalability: ensure that our product can handle 3x YoY growth 
• Accelerate time to value of new product capabilities
• Reduce the amount of manual work required to ingest vegetation analysis into our customer facing tools

At Overstory, our Staff Engineers are hands-on technical leaders whose influence extends beyond their team either through leading cross team initiatives, making technology choices for critical aspects of our technology platform or solving for critical technical challenges within teams enabling our business to achieve our rapid scaling plans (growing 3x YoY). 

This role will start off being primarily team scoped solving critical scaling challenges. There is scope to expand remit as we grow.

Time zone requirement: Europe (GMT/WET, CET, EET) and Eastern North America (NST, AST, EST)

What You'll Do

Technical Skills:

• Broad and deep understanding of system design with an ability to select the correct paradigm/technology given the situation and constraints.  
• Develops a deep understanding of our business domains and how technology can be applied to drive business impact. 
• Innovates and introduces new technologies or methodologies.
• Resolves complex technical challenges with innovative solutions.

Ownership:

• Leads cross-team initiatives or leads on architectural system design at team level
• Drives pragmatic technology choices/decisions making sensible trade offs in order to  balance current and future business needs.
• Defines coding standards and engineering best practices.
• Evaluates and recommends new tools and technologies.
• Hands-on contribution 

Leadership:

• Mentors and coaches engineers.
• Influences technical decisions at the organizational level.
• Collaborates with product managers and CTO to inform how technology can influence or enable the product strategy.

Skills & Experience

• Experience of working in a high growth scaleup environment 
• Product minded and able to demonstrate significant impact you have had on a business through the application of technology
• Proven experience of full stack development across the following (or similar) technologies: React/Typescript, Python/fastAPI, Postgres DB, Data pipelines)
• Comfortable working in a build it, run it environment (GCP, cloud run, grafana, k8s) - or similar
• Ability to design and implement scalable and resilient systems
• Strong leadership skills with the ability to mentor and coach engineers at all levels
• Excellent communication skills and ability to collaborate effectively in a cross-functional team environment
• Passion for learning and staying updated with evolving technologies and industry trends

Nice To Have

• Demonstrated experience scaling large distributed architectures
• Experience working in a remote-first environment
• Experience working with satellite data and/or imagery

Note: We believe that all people are capable of great things. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description.

What We Offer

• Competitive, location-specific compensation and benefits 
• Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around
• Home office stipend, coworking and ongoing education budgets 
• A company culture that genuinely embodies each of our core values
• To be part of truly mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve our climate crisis

At Graphcore, we’re building the future of AI compute.

We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.

As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.

Job Summary

As a Lab Support Engineer at Graphcore, you’ll play a key role in keeping our people and systems running efficiently. You’ll provide day-to-day support to internal customers and external collaborators in on-prem Hardware Labs and Silicon development projects in hybrid Linux & Windows environments. You will help colleagues resolve issues quickly while maintaining a strong focus on security and following established guidelines. 

The Team

You’ll be joining a multidisciplinary team with strong technical skills and a very encouraging culture. We work closely together and regularly share knowledge, and your skills will make a direct impact on our business. It’s an exciting and pivotal moment for us right now, with plenty of new projects ahead. If you're looking to solve interesting problems and see your work deliver real-world results, this is the team for you.

Responsibilities and Duties

• Logging and solving support requests face-to-face & via ticketing system, L1&L2 support
• Handling and maintaining Linux-based systems
• Handling and providing support for Windows-based systems
• Managing a fleet of servers, helping Hardware Lab teams with daily activities
• Installing and troubleshooting servers, hardware maintenance, fault finding
• Detailing solutions and maintaining a clear, up-to-date internal knowledge base

Essential

• Excellent communication and customer service skills
• Good understanding of troubleshooting principles and methodical problem-solving
• Strong Linux administration skills in Debian & RedHat derivatives
• Good Windows administration skills
• Good networking skills such as VLANs, VPNs, Wi-Fi, routing, subnetting
• Familiarity with desktop and server hardware, BMCs, Out-of-Band networks, firmware & BIOS upgrades, PDU, rack mounts
• Managing Infrastructure-as-Code using Puppet, Ansible, or similar

Desirable

• Experience with identifying network/storage/CPU/RAM bottlenecks across complex workloads
• Experience with various monitoring solutions and stack (e.g. Zabbix/Prometheus/Grafana Mimir/Open Telemetry)
• Experience in managing web servers, load-balancers, reverse-proxies (e.g.: ha-proxy, nginx)
• Proficiency with containerisation frameworks and orchestration (e.g.: Docker/containerd/Kubernetes)
• Python programming skills, with the ability to write code to interact with APIs, process data, and build small applications

We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.

At JetBrains, code is our passion. Ever since we started, back in 2000, we have strived to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

One of the projects we’re working on within the JetBrains Innovation Hub is the AppGlass, a product for safe, AI-first debugging of production systems. It will help engineering teams investigate issues in real environments with a strong focus on safety, reliability, security, low overhead, and practical AI integration. That means it’s a mix of JVM tooling, program analysis, and AI at the core. Check out our demo and website to get a better sense of how it works.

About the role

We are looking for a Senior Software Engineer with strong enterprise JVM experience. This role is a good fit for someone proactive and excited by complex engineering challenges at the intersection of production systems, developer tools, and AI agents.

In this role, you will:

• Design, build, and lead the development of product features.
• Develop tooling and automation for AI-first engineering workflows.
• Work on enterprise integrations and deployment scenarios across Kubernetes and cloud environments.
• Improve reliability, testing, performance, and security for production use.

We’d like to have you on the team if you:

• Have extensive experience with Java, Kotlin, and JVM systems.
• Have worked on enterprise backend software, infrastructure, or developer tooling.
• Are comfortable with Kubernetes and cloud environments.
• Take ownership, communicate clearly, and move things forward without waiting for perfect specs.
• Enjoy using AI in development, while validating results with solid engineering discipline.

We’ll be especially thrilled if you:

• Have experience with debugging, instrumentation, or observability-related tools.
• Have experience with .NET or Python backend products.
• Care deeply about developer productivity and engineering quality.

Why join JetBrains? 

• Strong base salary. We offer competitive pay that reflects your skills and experience.
• Flexible work location. Enjoy the freedom to work from home or from the office.
• Remote work. Spend up to 30 days per year working remotely from abroad.
• Extra time off. More days to relax, recharge, and do the things you love.
• Medical insurance allowance. Enjoy peace of mind for you and your family
• Learning and development opportunities. Access to conferences, courses, and language classes
• Language classes. Pick up the local language or sharpen your English skills.
• Fuel your day. Enjoy a hot meal or receive a lunch allowance on workdays.
• Mental health support. To help you feel your best, we provide easy access to professional mental health services.
• Sports benefit. Enjoy an on-site gym or sports club stipend.
• Internal events. Join company-wide celebrations and team gatherings.

*Some benefits may vary depending on location.

#LI-REMOTE 
#LI-KT1

Why Cast AI?

Cast AI is an automation platform that operates cloud-native and AI infrastructure at scale. By embedding autonomous decision-making directly into Kubernetes and cloud environments, Cast AI continuously optimizes performance, reliability, and efficiency in production.
The old way doesn't work. As Kubernetes and AI environments grow, manual decisions don’t. Cast AI replaces tickets, alerts, and manual tuning with continuous automation that adapts infrastructure as conditions change. Efficiency and cost savings follow naturally from that automation.
Over 2,100 companies already rely on Cast AI, including Akamai, BMW, Cisco, FICO, HuggingFace, NielsenIQ, Swisscom, and TGS.

Global team, diverse perspectives

We're headquartered in Miami, but our impact is international. We take a global and intentional approach to diversity. Today, Cast AI operates across 34 countries spanning Europe, North America, Latin America, and APAC, bringing a wide range of perspectives into how we build and lead.

Unicorn momentum

In January 2026, we achieved unicorn status with a strategic investment from Pacific Alliance Ventures, the corporate venture arm of Shinsegae Group (a $50+ billion Korean conglomerate). Our valuation now exceeds $1 billion, and we're just getting started.

Join us as we build the future of autonomous infrastructure.

About the role

Throughput. Latency. KV cache utilization.

Move those three numbers in the right direction, and two things happen: customers get faster, cheaper inference, and our margins improve. That's the entire thesis of this role. Every kernel you tune, every quantization scheme you ship, every scheduler tweak you land shows up directly in a customer's p99 and on our P&L.
This is a high-impact seat. It is also a high-autonomy seat as you'll be given the room to lead the technical direction of inference optimization at Kimchi, not execute someone else's roadmap.

The problem: running LLMs in production is a moving target. The "right" model and serving configuration for a workload depend on traffic shape, sequence-length distribution, batch dynamics, GPU SKU, memory bandwidth, quantization tolerance, and a dozen other variables that shift week to week. Most teams pick a model once, over-provision GPUs, and absorb the cost. Kimchi is the system that makes that decision automatically - continuously matching workloads to the most cost-efficient, best-performing LLM and serving configuration on a customer's infrastructure. We're building the optimization layer between the model and the hardware, and we need engineers who understand both sides deeply.

Stack

Python; vLLM; SGLang; TensorRT-LLM; PyTorch; CUDA-adjacent tooling; Kubernetes; gRP; ClickHouse; PostgreSQL; GCP Pub/Sub; AWS / GCP / Azure; GitLab CI; ArgoCD; Prometheus; Grafana; Loki; Tempo.

Requirements:

• 5+ years building real ML systems, with a portfolio that shows depth in inference or training infrastructure (not just model training notebooks).
• Strong Python - production services, not scripts.
• Hands-on experience with at least one of vLLM, SGLang, or TensorRT-LLM, and a working mental model of why an inference engine performs the way it does on a given GPU.
• Fluency with quantization tradeoffs - you've measured quality regressions, not just compression ratios.
• Comfort with distributed systems: collective communication, sharding strategies, and the practical failure modes of multi-GPU and multi-node setups.
• A bias toward measurement. You instrument before you optimize, and you can tell the difference between a real win and a benchmark artifact.
• Self-direction. This role comes with a wide mandate; you should be excited by that, not unsettled by it.

Responsibilities:

• Push throughput. Continuous batching, speculative decoding, chunked prefill, kernel-level tuning across vLLM, SGLang, and TensorRT-LLM. Find the ceiling on each GPU SKU, then raise it.
• Cut latency. Attack TTFT and TPOT separately. Profile, identify the actual bottleneck (compute, memory bandwidth, scheduling, networking), and fix it - not the bottleneck you assumed.
• Get more out of the KV cache. Paged attention, prefix caching, eviction policies, cache reuse across requests, quantized KV. This is where a lot of the unrealized throughput lives, and it's an area you'll own.
• Quantize without regressing quality. INT8, INT4, FP8 across weights, activations, and KV. Empirical work: measure quality on real workloads, not just perplexity benchmarks.
• Shrink cold starts and memory footprint. Faster init, smarter weight loading, tighter memory accounting - the difference between a model that scales and one that doesn't.
• Scale across nodes. Distributed inference topologies, network-aware placement, checkpointing strategies that don't bottleneck on storage or interconnect.
• Set the technical direction. Decide what we benchmark, what we adopt, and what we build ourselves. Bring the team along with strong writeups and reproducible experiments.

What’s in it for you?

• Competitive salary (depending on the level of experience).
• Enjoy a flexible, remote-first global environment.
• Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology
• Equity options.
• Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks.
• Spend 10% of your work time on personal projects or self-improvement. 
• Learning budget for professional and personal development - including access to international conferences and courses that elevate your skills.
• Annual hackathon to spark new ideas and strengthen team bonds.
• Team-building budget and company events to connect with your colleagues.
• Equipment budget to ensure you have everything you need.
• Extra days off to help maintain a healthy work-life balance.

Hiring process

• Screening call with Recruiter
• Hiring Manager interview
• Technical interview (system design)
• Live coding
• Culture Check interview with an executive

As part of our standard hiring process, we would like to inform you that a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr.
Please note that Cast AI does not provide any form of visa sponsorship/work permit.

#LI-Remote

Why Cast AI?

Cast AI is an automation platform that operates cloud-native and AI infrastructure at scale. By embedding autonomous decision-making directly into Kubernetes and cloud environments, Cast AI continuously optimizes performance, reliability, and efficiency in production.

The old way doesn't work. As Kubernetes and AI environments grow, manual decisions don’t. Cast AI replaces tickets, alerts, and manual tuning with continuous automation that adapts infrastructure as conditions change. Efficiency and cost savings follow naturally from that automation.

Over 2,100 companies already rely on Cast AI, including Akamai, BMW, Cisco, FICO, HuggingFace, NielsenIQ, Swisscom, and TGS.

Global team, diverse perspectives
We're headquartered in Miami, but our impact is international. We take a global and intentional approach to diversity. Today, Cast AI operates across 34 countries spanning Europe, North America, Latin America, and APAC, bringing a wide range of perspectives into how we build and lead. 

Unicorn momentum
In January 2026, we achieved unicorn status with a strategic investment from Pacific Alliance Ventures, the corporate venture arm of Shinsegae Group (a $50+ billion Korean conglomerate). Our valuation now exceeds $1 billion, and we're just getting started.

Join us as we build the future of autonomous infrastructure.

Kimchi is an open-source AI inference platform built for teams running serious agentic coding workloads. We're building the harness, the routing, and the infrastructure layer that makes running your own AI coding stack possible - and affordable. We're early, moving fast, and the developer community is central to how we grow.

Responsibilities:

• Build things publicly with Kimchi - tutorials, demos, integrations - that show developers how to solve real problems. Think live build logs, OSS integrations, or benchmarks you'd want to read yourself.
• Be the voice of the the developer community: Discord, GitHub discussions, Reddit, HN - be present where developers are already talking about the problems we solve
• Be the structured feedback loop between dev community and product - synthesize what you're hearing into actionable signals for the product team. 
• Write technical content that ranks and spreads: setup guides, benchmark breakdowns, comparison posts, integration walkthroughs
• Speak at conferences, meetups and run workshops - representing Kimchi as a technical peer
• Identify where new users get stuck and advocate hard for fixes
• Help shape Kimchi's voice in the developer community - what we stand for, what we say when there is trending news in the market 

Requirements:

• You've built real software and can talk about it credibly - ideally you've used agentic coding tools and have opinions about them
• You're a strong technical writer - you can explain complex things clearly and make them resonate with the developer audience
• You're comfortable being the public face of a technical product: blog posts, talks, live demos, community threads
• Huge plus: You'd have tested and found problems Kimchi solves interesting -  before this job posting even existed
• Bonus: you've worked in or around Kubernetes, LLM inference, or developer tooling

What’s in it for you?

• Enjoy a flexible, remote-first global environment.
• Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology.
• Equity options.
• Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks.
• Spend 10% of your work time on personal projects or self-improvement. 
• Learning budget for professional and personal development - including access to international conferences and courses that elevate your skills.
• Team-building budget and company events to connect with your colleagues.
• Equipment budget to ensure you have everything you need.
• Extra days off to help maintain a healthy work-life balance.

Hiring process

• Screening call with Recruiter
• Hiring Manager interview
• 1-2 additional interviews based on the role
• Culture Check interview with an executive

*As part of our standard hiring process, we would like to inform you that a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr.
*Please note that Cast AI does not provide any form of visa sponsorship/work permit.
#LI-Remote