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Location: United Kingdom; Ireland; Poland Workplace: Remote As a Staff Software Engineer on Coder’s Agentic Engineering team, you’ll shape the systems behind our agentic development experience. You’ll work across the agent harness, integrations, and workflows that connect agents with real development environments. You’ll stay hands-on while setting the team's technical direction. You’ll lead complex work, make sound architectural decisions, and help other engineers do their best work. WHAT YOU’LL DO HERE - Set technical direction across Coder’s agent harness, integrations, and workflows. - Design and build production systems in Go, with work across React and TypeScript where needed. - Evolve agent execution, tool use, context management, streaming, and long-running workflows. - Extend our provider-agnostic architecture as models and capabilities change. - Lead complex projects from early ambiguity through production. - Raise the engineering bar through design reviews, code reviews, and technical mentorship. - Partner with Product and Design on clear, useful agent experiences. - Improve the reliability, performance, and operability of agentic systems. WHAT WE’RE LOOKING FOR - Deep experience building and operating production software systems. - Strong hands-on experience with Go. - Experience with React and TypeScript. - Hands-on experience building systems around LLMs and agentic workflows. - Experience with model APIs, tool calling, context management, or agent loops. - Strong distributed systems knowledge. - Working knowledge of AWS. - A track record of setting technical direction without formal authority. - Strong architectural judgment and comfort working through ambiguity. - Someone who makes the engineers around them better. OUR TECH STACK - Backend: Go, Postgres - Frontend: TypeScript, React - Infrastructure: AWS, Kubernetes - Observability: Prometheus, Grafana - CI/CD: GitHub Actions BONUS TACOS IF YOU HAVE - (Tacos? If you need an ice-breaker, ask how we say thanks by giving tacos!) - Experience building coding agents, developer tools, or cloud development environments. - Experience with agent tools, or multi-agent systems. - Experience building abstractions across multiple model providers. - Deep experience with AWS, Kubernetes, Docker and Linux. - Open-source contributions or experience working directly with customers. Coder’s agentic architecture is provider-agnostic. The foundation is already built; this role helps decide how it evolves, where we invest, and how we keep it reliable as the space moves quickly. ABOUT CODER Coder is the leading platform for AI development Infrastructure, enabling enterprises to securely run human and AI-driven development workflows in consistent, governed environments. Coder provides self-hosted, agent-ready workspaces that unify developer productivity and platform governance. With Coder, enterprises can confidently evolve from human-only development to AI-assisted and autonomous workflows, without sacrificing security, compliance, or performance. Learn more at coder.com http://coder.com. INTERVIEW PROCESS  We believe that the interview process should be transparent, consistent, and enjoyable. We value your time and hope to complete the interview process in two to four weeks, if schedules allow. Through your interviews, you will meet a mix of individual contributors, managers, and senior leaders. AI USE DURING THE INTERVIEW PROCESS As an AI company, Coder embraces the use of AI tools, and we want to be transparent about our expectations as you navigate our interview process. Not permitted: Using AI assistance during conversational interviews. Permitted: Using AI tooling for take-home assessments. Please flag where and to what extent it was used in your take-home. Your submission will not be penalized for using AI as long as it is done honestly. OUR USE OF AI IN HIRING We use AI tools to help manage our recruitment process efficiently and fairly. Specifically: - Ashby and Brainerr help us review inbound applications by surfacing candidates who best match the role requirements we've defined. This tool does not make hiring decisions; it helps our team prioritize which applications to review first. - Granola takes notes during our interview calls so our team can focus on the conversation with you. All hiring decisions are made by humans. Our team reviews applications, conducts interviews, and makes final selections. AI tools assist us but never replace human judgment, and these practices are conducted in compliance with applicable data protection, AI governance, and labor laws. Your data is not used to train AI models. In accordance with New York City Local Law 144, an independent bias audit has been conducted on "Automated Employment Decision Tools"; results are available for Ashby https://www.ashbyhq.com/downloadables/ashby-bias-audit-08-2024.pdf. If you're applying for a role at Coder and have questions about how we use AI in our process, or if you'd like to request information about the data we collect, please contact careers@coder.com.   CODER IS A PROUD EQUAL OPPORTUNITY EMPLOYER We are committed to providing equal employment opportunities to qualified applicants and do not discriminate on the basis of race, color, ancestry, religion, sex, pregnancy, gender, gender identity, gender expression, sexual orientation, national origin, age, marital status, genetic information, disability, protected veteran status or any other characteristic protected by federal, state, or local laws.

Location: United States, San Mateo, CA Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. PlayStation isn’t just the Best Place to Play — it’s also the Best Place to Work. Today, we’re recognized as a global leader in entertainment producing The PlayStation family of products and services including PlayStation®5, PlayStation®4, PlayStation®VR, PlayStation®Plus, acclaimed PlayStation software titles from PlayStation Studios, and more. PlayStation also strives to create an inclusive environment that empowers employees and embraces diversity. We welcome and encourage everyone who has a passion and curiosity for innovation, technology, and play to explore our open positions and join our growing global team. The PlayStation brand falls under Sony Interactive Entertainment, a wholly-owned subsidiary of Sony Corporation. Staff Software Engineer – Data Do you want to join a team of talented engineers building the next generation of real-time data platforms that power analytics and data-driven experiences across PlayStation? As part of our Data Platform team, you will play a key technical leadership role in designing and evolving the Real-Time Analytics Platform (RTAP), enabling high-throughput, low-latency analytics and stream processing at PlayStation scale. The Software Engineers within our Platform Engineering Group design, build, document, and operate large-scale distributed data platforms that support real-time and near real-time analytics across PlayStation. You will solve complex distributed systems challenges, evolve our streaming and analytics architecture, integrate AI-powered platform capabilities, and improve scalability, reliability, performance, and developer productivity. We’re looking for someone who is passionate about distributed systems, real-time analytics, and building scalable data platforms. You will work closely with Engineering, Product, Infrastructure, Security, and Data Engineering teams to shape technical strategy, influence architecture across organizations, mentor engineers, and help drive the long-term evolution of PlayStation’s data platform. Responsibilities · Design, build, and operate large-scale distributed data systems that power real-time and near real-time analytics,, and data-driven applications across PlayStation. · Lead the architecture and evolution of RTAP’s stream processing and analytics platforms, improving scalability, reliability, performance, and developer productivity. · Own critical platform capabilities end-to-end from architecture and implementation through production operations, performance optimization, reliability, and lifecycle management. · Build and optimize distributed data services using technologies such as Apache Flink, Spark Structured Streaming, ClickHouse, and Apache Druid to support high-throughput, low-latency workloads. · Partner with Data Engineering teams to integrate batch and streaming workloads using modern lakehouse architectures and build interoperable, scalable data platforms. · Build AI-powered capabilities to automate engineering workflows, improve data quality, simplify platform operations, accelerate troubleshooting, and enhance developer productivity. · Establish technical standards and engineering best practices for distributed systems, stream processing, data modeling, query optimization and platform reliability. · Mentor engineers across the organization by reviewing architecture, designs, and code while raising the technical bar through coaching and technical leadership. · Partner with Product, Infrastructure, Security, and Platform Engineering teams to define long-term technical strategy and deliver scalable platform capabilities aligned with business priorities. · Investigate and resolve complex production challenges involving high-throughput, low-latency distributed systems, ensuring high availability and operational excellence. · Participate in the team's production support and on-call rotation, leading incident response, conducting root-cause analysis, and implementing reliability improvements that strengthen the platform over time · Evaluate emerging technologies and distributed data platforms, recommending investments that improve scalability, reliability, developer productivity, and cost efficiency. Requirements · Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. · 8+ years of experience designing and building large-scale distributed systems, with expertise in real-time data processing, analytics, or data platform engineering. · Strong proficiency in Python , with experience building production-grade distributed systems and data processing applications. Experience with Scala is beneficial for supporting and evolving existing platform components. · Hands-on expertise designing and operating large-scale stream processing applications using Apache Flink , Apache Spark Structured Streaming , or equivalent distributed streaming technologies. · Production experience designing, operating, and optimizing distributed analytics platforms using ClickHouse , Apache Druid , or equivalent high-performance OLAP/analytics databases, including query optimization, data modeling, and performance tuning at scale. · Experience building and consuming event-driven data pipelines using AWS MSK , Apache Kafka , or equivalent messaging platforms, with a focus on developing reliable, scalable data processing applications. · Experience applying AI/ML techniques and modern AI tooling to automate engineering workflows, improve data pipelines, simplify platform operations, and enhance developer productivity. · Strong systems design skills with the ability to evaluate architectural trade-offs across scalability, latency, throughput, consistency, reliability, and cost. · Demonstrated technical leadership through architecture ownership, mentoring engineers, and influencing technical decisions across multiple teams. Nice to Have · Experience with Databricks , Apache Iceberg , or modern lakehouse architectures, with the ability to design and integrate batch and streaming workloads into scalable, production-grade data platforms. · Experience building or operating multi-tenant, self-service data platforms supporting multiple engineering organizations. · Experience collaborating with globally distributed engineering teams across multiple organizations and time zones to deliver shared platform capabilities and drive technical alignment. Your First 90 Days 30 Days: Develop a strong understanding of the platform’s architecture, capabilities, engineering practices, and roadmap.Begin contributing to architecture discussions, feature development, design reviews, and production support.Build relationships within the team as well as across  the Data Platform organization. 60 Days: Take technical ownership of a major platform capability or architectural area. Identify opportunities to improve scalability, performance, reliability, or developer productivity.Collaborate with Data Engineering, Infrastructure, Product, and other partner teams on cross-platform initiatives. 90 Days: Lead the design and delivery of key roadmap initiatives for the team..Influence technical direction across teams and mentor engineers on distributed systems and platform engineering best practices.Establish clear architectural recommendations for the next phase of the platform’s evolution. In 90 days, you will have a detailed understanding of the Real-Time Analytics Platform and its role within PlayStation’s broader data ecosystem. You will be comfortable owning complex distributed systems initiatives, partnering closely with Product and Engineering teams, and driving large-scale solutions from architecture through production delivery. At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location. Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location. In addition, this role is eligible for SIE’s top-tier benefits package that includes medical, dental, vision, matching 401(k), paid time off, wellness program and coveted employee discounts for Sony products. This role also may be eligible for a bonus package. Click here to learn more. The estimated base pay range for this role is listed below. $198,200 — $297,400 USD Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice (where applicable) for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Location: Remote - Europe About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role This position sits within Nebius Token Factory, our serverless platform for running and customizing open-source LLMs in production. Token Factory allows for serverless inference and fine-tuning backed by in-house optimizations like custom speculative decoding, quantization, cache-aware routing and dedicated endpoints. Customers come to us to move from prototype to scaled production without the cost and complexity of building and tuning their own inference stack. Our Solutions Architects own the technical delivery of customer engagements: deploying open-source models, tuning the serving stack, benchmarking against the customer's success criteria, and carrying the technical relationship through to production. Sales Engineers qualify and scope the opportunity; SAs execute it. Technical Account Managers take it from production onward. We're looking for a Manager, ML Solutions Architecture to lead our EU regional SA teams. Your scope is PoC delivery and post-sales technical support : the people who do it, the standard they do it to, and the operating cadence that keeps it predictable. You will report to the Head of Solutions Architecture and partner with a peer manager in the other region. We expect you to push people when they need pushing, make the uncomfortable call when deliverables don't land even though the effort was real, and take ownership of the documentation work: implement and monitor the following of the guidelines, ticket hygiene, and making sure the team actually uses all three. You're welcome to work remotely from any EU country. Your responsibilities will include: Lead the team Manage a team of 8 Solutions Architects, with continued growth planned: 1:1s, goal setting, performance reviews, promotion cases, and individual growth plans Build an accurate picture of each SA's strengths, gaps, and preferences, and allocate accounts and engagements against both expertise and interest Run the cadence that surfaces blockers early, then take them to the development, product, and business teams that can clear them, and stay on them until they do Hold people to outcomes: distinguish effort from delivered results, say so plainly when the two diverge, and reflect it in ratings and compensation decisions Onboard new joiners through to their first independently delivered engagement Coach SAs into stronger engineers and stronger communicators, and make deliberate calls about who is ready for more scope Own delivery Be accountable for your team's delivery outcomes: time from PoC kick-off to first optimized dedicated endpoint, success-criteria hit rate, and the quality of the technical relationship after the customer goes to production Review technical work before it reaches the customer: benchmarking methodology, serving configurations, results, closure documents; catch the wrong conclusion drawn from a metrics artifact before a customer sees it Ensure staffing and escalation coverage across accounts and timezones, including post-sales request load that does not respect sprint boundaries Call infeasibility early and with evidence, rather than letting the team burn iterations against requirements the platform cannot meet today Own the operating system of the team Maintain and extend the team's documentation: responsibilities, runbooks, guides, onboarding, definitions of done, engagement closure templates. Keep it accurate and reachable; link, don't copy Get it used , not just written: documentation nobody reads is a cost, not an asset Keep the ticket tracker the system of record, so PoC and production status is readable without asking anyone Instrument the work: define and report the metrics that show whether delivery is getting faster and more reliable over time Work across teams Development and research teams: convert recurring customer pain into prioritized platform work, and represent the customer's technical reality in roadmap discussions Pre-sales: hold the scoping-to-execution boundary: push back on under-scoped engagements, and feed feasibility signal back upstream Account management: make production handoffs uneventful, and keep post-sales technical requests moving Business and leadership: give a straight read on account health, technical feasibility, and capacity needs We expect you to have: 3+ years managing technical teams, including performance management and difficult conversations Experience managing a customer-facing team. Running a team whose work is visible to customers, on customer timelines, with customer escalations. Strong ML knowledge: LLM architectures, fine-tuning approaches (SFT/LoRA, RL-based), evaluation design, and a working command of inference internals — quantization, KV-cache management, batching, routing, speculative decoding — and of the frameworks the team works in (vLLM, SGLang, TensorRT-LLM) Enough technical judgment to review someone else's benchmark and find the flaw in the methodology, not just in the conclusion Python strong enough to read and review your team's code Excellent communication skills, with the ability to clearly explain technical concepts to diverse audiences, from engineers to executives, including in front of enterprise customers under pressure Genuine tolerance for operational work: documentation, process design, reporting, and the follow-through that makes them stick Comfort operating with ambiguity across distributed teams and timezones, and a bias toward writing things down It would be an added bonus if you have: References from both former managers and former direct reports Experience scaling a team through rapid growth (5 → 15+) without losing delivery quality Prior experience in a customer-facing technical function at a cloud, inference, or AI infrastructure provider Experience defining process and documentation for a team that had none Hands-on background running LLMs in production and debugging inference workloads at the framework level Work with multimodal AI models (vision-language, speech) Proficiency with DevOps tooling (Docker, Kubernetes) and infrastructure-as-code Preferred technical stack: Programming languages: Python ML frameworks and libraries: vLLM, TensorRT-LLM, SGLang, Transformers, OpenAI/Anthropic SDKs MLOps and DevOps tools: Kubernetes (K8s), Docker, Git Cloud platforms: AWS (SageMaker, Bedrock), GCP (Vertex AI), Azure (Azure ML) Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Location: Remote - United States About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role This position sits within Nebius Token Factory, our serverless platform for running and customizing open-source LLMs in production. Token Factory allows for serverless inference and fine-tuning backed by in-house optimizations like custom speculative decoding, quantization, cache-aware routing and dedicated endpoints. Customers come to us to move from prototype to scaled production without the cost and complexity of building and tuning their own inference stack. Our Solutions Architects own the technical delivery of customer engagements: deploying open-source models, tuning the serving stack, benchmarking against the customer's success criteria, and carrying the technical relationship through to production. Sales Engineers qualify and scope the opportunity; SAs execute it. Technical Account Managers take it from production onward. We're looking for a Manager, ML Solutions Architecture to lead our US regional SA teams. Your scope is PoC delivery and post-sales technical support : the people who do it, the standard they do it to, and the operating cadence that keeps it predictable. You will report to the Head of Solutions Architecture and partner with a peer manager in the other region. We expect you to push people when they need pushing, make the uncomfortable call when deliverables don't land even though the effort was real, and take ownership of the documentation work: implement and monitor the following of the guidelines, ticket hygiene, and making sure the team actually uses all three. You're welcome to work remotely from the United States. Your responsibilities will include: Lead the team Manage a team of 4 Solutions Architects, with continued growth planned: 1:1s, goal setting, performance reviews, promotion cases, and individual growth plans Build an accurate picture of each SA 's strengths, gaps, and preferences, and allocate accounts and engagements against both expertise and interest Run the cadence that surfaces blockers early, then take them to the development, product, and business teams that can clear them, and stay on them until they do Hold people to outcomes: distinguish effort from delivered results, say so plainly when the two diverge, and reflect it in ratings and compensation decisions Onboard new joiners through to their first independently delivered engagement Coach SAs into stronger engineers and stronger communicators, and make deliberate calls about who is ready for more scope Own delivery Be accountable for your team's delivery outcomes: time from PoC kick-off to first optimized dedicated endpoint, success-criteria hit rate, and the quality of the technical relationship after the customer goes to production Review technical work before it reaches the customer: benchmarking methodology, serving configurations, results, closure documents; catch the wrong conclusion drawn from a metrics artifact before a customer sees it Ensure staffing and escalation coverage across accounts and timezones, including post-sales request load that does not respect sprint boundaries Call infeasibility early and with evidence, rather than letting the team burn iterations against requirements the platform cannot meet today Own the operating system of the team Maintain and extend the team's documentation: responsibilities, runbooks, guides, onboarding, definitions of done, engagement closure templates. Keep it accurate and reachable; link, don't copy Get it used , not just written: documentation nobody reads is a cost, not an asset Keep the ticket tracker the system of record, so PoC and production status is readable without asking anyone Instrument the work: define and report the metrics that show whether delivery is getting faster and more reliable over time Work across teams Development and research teams: convert recurring customer pain into prioritized platform work, and represent the customer's technical reality in roadmap discussions Pre-sales: hold the scoping-to-execution boundary: push back on under-scoped engagements, and feed feasibility signal back upstream Account management: make production handoffs uneventful, and keep post-sales technical requests moving Business and leadership: give a straight read on account health, technical feasibility, and capacity needs We expect you to have: 3+ years managing technical teams, including performance management and difficult conversations Experience managing a customer-facing team. Running a team whose work is visible to customers, on customer timelines, with customer escalations. Strong ML knowledge: LLM architectures, fine-tuning approaches ( SFT / LoRA , RL -based), evaluation design, and a working command of inference internals — quantization, KV -cache management, batching, routing, speculative decoding — and of the frameworks the team works in (vLLM, SGLang, TensorRT-LLM) Enough technical judgment to review someone else's benchmark and find the flaw in the methodology, not just in the conclusion Python strong enough to read and review your team's code Excellent communication skills, with the ability to clearly explain technical concepts to diverse audiences, from engineers to executives, including in front of enterprise customers under pressure Genuine tolerance for operational work: documentation, process design, reporting, and the follow-through that makes them stick Comfort operating with ambiguity across distributed teams and timezones, and a bias toward writing things down It would be an added bonus if you have: References from both former managers and former direct reports Experience scaling a team through rapid growth (5 → 15+) without losing delivery quality Prior experience in a customer-facing technical function at a cloud, inference, or AI infrastructure provider Experience defining process and documentation for a team that had none Hands-on background running LLMs in production and debugging inference workloads at the framework level Work with multimodal AI models (vision-language, speech) Proficiency with DevOps tooling (Docker, Kubernetes) and infrastructure-as-code Preferred technical stack: Programming languages: Python ML frameworks and libraries: vLLM, TensorRT-LLM, SGLang, Transformers, OpenAI/Anthropic SDKs MLOps and DevOps tools: Kubernetes (K8s), Docker, Git Cloud platforms: AWS (SageMaker, Bedrock), GCP (Vertex AI), Azure (Azure ML) Pay Transparency We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law. Base Compensation Range $228,000 — $285,000 USD Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Location: Berlin, Germany; Helsinki, Finland About Wolt At Wolt, we create technology that brings joy, simplicity and earnings to the neighborhoods of the world. In 2014 we started with delivery of restaurant food. Now we’re building the delivery of (almost) everything and you’ll find us in over 500 cities in 30 countries around the world. In 2022 we joined forces with DoorDash and together we keep on dreaming big and expanding across the globe. Working at Wolt isn’t always easy, but it’s definitely exciting. Here you’ll learn more, build more, and ship more than in most other companies. You’ll be challenged a lot, but also have a lot of fun on the way. So, if you’re a self-starter with drive and entrepreneurial spirit, this could be the ride of your life. About the Team Merchant EMEA Engineering builds the technology that helps merchants join, grow, and operate successfully across our markets. Our organization brings together the strengths of Wolt and Deliveroo and supports merchants across 37 countries. We work across the merchant journey, including onboarding, business growth and support, analytics and recommendations, menu and order management, integrations, and merchant applications. Our teams sit close to the business. Rather than primarily building foundational platforms, we build products and features on top of our existing platforms to solve real merchant and market needs, including local business requirements, growth opportunities, and operational challenges. 📍This open role is based in our tech hubs in Helsinki or Berlin . Please note: This role requires being based in Berlin/Helsinki on a hybrid basis. We are currently unable to offer fully remote work, visa sponsorship, or relocation support for this opportunity. What You'll Do As a Fullstack Engineer, you'll contribute to products and services used across the merchant experience. You'll: Build and maintain production software across backend services and user-facing applications. Work on areas such as merchant onboarding, analytics, recommendations, menu and order management, integrations, or merchant-facing tools. Develop reliable APIs, data models, services, and user-facing features. Collaborate closely with product managers, designers, operations, and other engineers to turn business needs into practical technical solutions. Own features from implementation through production and ongoing maintenance. Contribute to technical design discussions and improve the quality, scalability, observability, and maintainability of our systems. Use AI-assisted development tools effectively as part of your engineering workflow, while critically evaluating their output and taking ownership of the final solution. Be willing to work outside your primary area of expertise when needed to solve the problem end-to-end. How We Work Ownership: Engineers take responsibility for the features and services they work on, from development to production. Collaboration: We work closely across engineering, product, design, data, and operations. Pragmatism: We value simple and maintainable solutions that create business impact without unnecessary complexity. Flexibility: We care more about solving the problem than strict frontend or backend boundaries. Our Tech Stack Our backend services primarily use Go and Kotlin , while our frontend applications use technologies such as TypeScript and React . We also work with technologies including Kafka, PostgreSQL, MongoDB, Redis, AWS, Kubernetes, Docker, gRPC, and modern cloud infrastructure. Our Humble Expectations We're looking for engineers who have: An AI-first mindset, with a deep experience in leveraging modern AI tools and solid engineering principles to solve problems end-to-end, independently of any specific technology stack. Proven experience building production software in backend, frontend, or fullstack environments end-to-end and at scale. Strong expertise in at least one area of the stack, with a willingness to contribute outside that area when needed. Experience with a modern backend language such as Go, Kotlin, Java, or similar, and/or modern frontend technologies such as TypeScript and React. Good understanding of APIs, databases, testing, and software design fundamentals. The ability to work independently on well-scoped problems and collaborate effectively with others. Good communication skills and a pragmatic, collaborative mindset. You do not need to be equally strong in frontend and backend. We welcome different balances of experience. You might be primarily a backend engineer who is comfortable making frontend changes when needed, or a frontend-focused engineer who is happy to work with APIs and backend services. What matters most is that you are comfortable working across boundaries to deliver the right solution. Nice to Have Experience in one or more of the following areas would be a plus: Merchant-facing or internal operational tools. Analytics, recommendations, or decisioning systems. Grocery, retail, restaurants, logistics, or marketplace technology. Integrations with external business systems. Kafka or other streaming technologies. Cloud infrastructure such as AWS, Kubernetes, or Docker. Why Join Us? You'll work on products that directly affect how merchants interact with Wolt Deliveroo and DoorDash across Europe. The scope is broad and close to the business, giving you the opportunity to work on meaningful problems across different parts of the merchant journey while developing your skills across the stack. You can read more about our recruitment process here. here . Our Commitment to Diversity and Inclusion We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel. Beware of recruitment scams: DoorDash, Deliveroo, and Wolt will never ask you to pay money or share sensitive financial information during hiring — learn more about our legitimate recruiting process at Recruitment Scam Awareness - DoorDash .

Location: Serbia Job Title: AI/ML Engineer Department: IT Services /IT Infrastructure Reports To: IT Project Manager Job Overview: The AI/ML Engineer plays a critical role in designing, developing, and deploying machine learning models and AI-driven solutions to support strategic business initiatives. The role involves collaborating with cross-functional teams, including software engineering, data analytics, product development, and business stakeholders, to drive intelligent automation, data-driven decision-making, and advanced analytics capabilities. The ideal candidate will have 3 to 5 years of experience in AI/ML model development, with a strong foundation in machine learning algorithms, data preprocessing, and deployment pipelines. Experience with Python, TensorFlow/PyTorch, and cloud-based ML services is essential. Responsibilities: 1. Model Development and Optimization Design, build, and deploy ML models for classification, regression, NLP, computer vision, or time-series forecasting. Select appropriate algorithms and techniques based on business needs and data characteristics. Continuously monitor and improve model performance using metrics and feedback loops. 2. Data Preparation and Feature Engineering Clean, preprocess, and transform structured and unstructured datasets for training and inference. Engineer and select relevant features to improve model accuracy and generalizability. Collaborate with data engineers to ensure data quality and accessibility. 3. Model Deployment and MLOps Package and deploy models using tools like Docker, Flask/FastAPI, and Kubernetes. Implement CI/CD pipelines for ML using platforms like MLflow, Airflow, or Kubeflow. Monitor deployed models for drift, latency, and performance in production environments. 4. AI Solutions and Use Case Implementation Work with business stakeholders to translate real-world problems into AI/ML use cases. Prototype and test AI-driven solutions (e.g., recommendation engines, chatbots, fraud detection). Contribute to proof-of-concept projects and assist in scaling successful models to production. 5. Research and Innovation Stay updated with the latest research, frameworks, and tools in machine learning and AI. Experiment with cutting-edge models (e.g., LLMs, transformers, generative AI) and assess their viability. Promote innovation by recommending and implementing modern AI strategies. 6. Cross-functional Collaboration Collaborate with software developers, DevOps, data analysts, and domain experts for end-to-end solution delivery. Translate technical insights into business value through clear documentation and presentations. 7. Documentation and Best Practices Maintain comprehensive documentation for models, experiments, and pipelines. Ensure reproducibility, scalability, and compliance with data governance policies. Requirements: Experience: 3–5 years of hands-on experience in machine learning model development and deployment. Proven track record of solving real-world problems using supervised, unsupervised, or deep learning methods. Technical Skills: Strong knowledge of: Python and ML libraries (scikit-learn, pandas, NumPy, TensorFlow/PyTorch) Model evaluation, hyperparameter tuning, and pipeline automation REST APIs for model serving and integration Familiarity with: MLOps tools (MLflow, Airflow, DVC, Docker, Kubernetes) Cloud ML services (AWS SageMaker, Azure ML, GCP AI Platform) NLP or computer vision frameworks (e.g., Hugging Face, OpenCV) Soft Skills: Strong analytical and problem-solving abilities. Excellent communication skills, both verbal and written. Ability to work independently and within cross-functional teams. Curiosity, adaptability, and willingness to learn continuously.

Location: Romania Job Title: AI/ML Engineer Department: IT Services Reports To: IT Project Manager Job Overview: The AI/ML Engineer plays a critical role in designing, developing, and deploying machine learning models and AI-driven solutions to support strategic business initiatives. The role involves collaborating with cross-functional teams, including software engineering, data analytics, product development, and business stakeholders, to drive intelligent automation, data-driven decision-making, and advanced analytics capabilities. The ideal candidate will have 3 to 5 years of experience in AI/ML model development, with a strong foundation in machine learning algorithms, data preprocessing, and deployment pipelines. Experience with Python, TensorFlow/PyTorch, and cloud-based ML services is essential. Responsibilities: 1. Model Development and Optimization Design, build, and deploy ML models for classification, regression, NLP, computer vision, or time-series forecasting. Select appropriate algorithms and techniques based on business needs and data characteristics. Continuously monitor and improve model performance using metrics and feedback loops. 2. Data Preparation and Feature Engineering Clean, preprocess, and transform structured and unstructured datasets for training and inference. Engineer and select relevant features to improve model accuracy and generalizability. Collaborate with data engineers to ensure data quality and accessibility. 3. Model Deployment and MLOps Package and deploy models using tools like Docker, Flask/FastAPI, and Kubernetes. Implement CI/CD pipelines for ML using platforms like MLflow, Airflow, or Kubeflow. Monitor deployed models for drift, latency, and performance in production environments. 4. AI Solutions and Use Case Implementation Work with business stakeholders to translate real-world problems into AI/ML use cases. Prototype and test AI-driven solutions (e.g., recommendation engines, chatbots, fraud detection). Contribute to proof-of-concept projects and assist in scaling successful models to production. 5. Research and Innovation Stay updated with the latest research, frameworks, and tools in machine learning and AI. Experiment with cutting-edge models (e.g., LLMs, transformers, generative AI) and assess their viability. Promote innovation by recommending and implementing modern AI strategies. 6. Cross-functional Collaboration Collaborate with software developers, DevOps, data analysts, and domain experts for end-to-end solution delivery. Translate technical insights into business value through clear documentation and presentations. 7. Documentation and Best Practices Maintain comprehensive documentation for models, experiments, and pipelines. Ensure reproducibility, scalability, and compliance with data governance policies. Requirements: Experience: 3–5 years of hands-on experience in machine learning model development and deployment. Proven track record of solving real-world problems using supervised, unsupervised, or deep learning methods. Technical Skills: Strong knowledge of: Python and ML libraries (scikit-learn, pandas, NumPy, TensorFlow/PyTorch) Model evaluation, hyperparameter tuning, and pipeline automation REST APIs for model serving and integration Familiarity with: MLOps tools (MLflow, Airflow, DVC, Docker, Kubernetes) Cloud ML services (AWS SageMaker, Azure ML, GCP AI Platform) NLP or computer vision frameworks (e.g., Hugging Face, OpenCV) Soft Skills: Strong analytical and problem-solving abilities. Excellent communication skills, both verbal and written. Ability to work independently and within cross-functional teams. Curiosity, adaptability, and willingness to learn continuously.

Location: India Job Title: AI/ML Engineer Department: IT Services Reports To: IT Project Manager Job Overview: The AI/ML Engineer plays a critical role in designing, developing, and deploying machine learning models and AI-driven solutions to support strategic business initiatives. The role involves collaborating with cross-functional teams, including software engineering, data analytics, product development, and business stakeholders, to drive intelligent automation, data-driven decision-making, and advanced analytics capabilities. The ideal candidate will have 3 to 5 years of experience in AI/ML model development, with a strong foundation in machine learning algorithms, data preprocessing, and deployment pipelines. Experience with Python, TensorFlow/PyTorch, and cloud-based ML services is essential. Responsibilities: 1. Model Development and Optimization Design, build, and deploy ML models for classification, regression, NLP, computer vision, or time-series forecasting. Select appropriate algorithms and techniques based on business needs and data characteristics. Continuously monitor and improve model performance using metrics and feedback loops. 2. Data Preparation and Feature Engineering Clean, preprocess, and transform structured and unstructured datasets for training and inference. Engineer and select relevant features to improve model accuracy and generalizability. Collaborate with data engineers to ensure data quality and accessibility. 3. Model Deployment and MLOps Package and deploy models using tools like Docker, Flask/FastAPI, and Kubernetes. Implement CI/CD pipelines for ML using platforms like MLflow, Airflow, or Kubeflow. Monitor deployed models for drift, latency, and performance in production environments. 4. AI Solutions and Use Case Implementation Work with business stakeholders to translate real-world problems into AI/ML use cases. Prototype and test AI-driven solutions (e.g., recommendation engines, chatbots, fraud detection). Contribute to proof-of-concept projects and assist in scaling successful models to production. 5. Research and Innovation Stay updated with the latest research, frameworks, and tools in machine learning and AI. Experiment with cutting-edge models (e.g., LLMs, transformers, generative AI) and assess their viability. Promote innovation by recommending and implementing modern AI strategies. 6. Cross-functional Collaboration Collaborate with software developers, DevOps, data analysts, and domain experts for end-to-end solution delivery. Translate technical insights into business value through clear documentation and presentations. 7. Documentation and Best Practices Maintain comprehensive documentation for models, experiments, and pipelines. Ensure reproducibility, scalability, and compliance with data governance policies. Requirements: Experience: 3–5 years of hands-on experience in machine learning model development and deployment. Proven track record of solving real-world problems using supervised, unsupervised, or deep learning methods. Technical Skills: Strong knowledge of: Python and ML libraries (scikit-learn, pandas, NumPy, TensorFlow/PyTorch) Model evaluation, hyperparameter tuning, and pipeline automation REST APIs for model serving and integration Familiarity with: MLOps tools (MLflow, Airflow, DVC, Docker, Kubernetes) Cloud ML services (AWS SageMaker, Azure ML, GCP AI Platform) NLP or computer vision frameworks (e.g., Hugging Face, OpenCV) Soft Skills: Strong analytical and problem-solving abilities. Excellent communication skills, both verbal and written. Ability to work independently and within cross-functional teams. Curiosity, adaptability, and willingness to learn continuously.

Location: Poland Job Overview We are seeking an experienced Software QA & Testing Engineer to join our dynamic team. In this role, you will play a crucial part in ensuring the delivery of high-quality software through robust manual and automated testing processes, as well as adopting modern testing tools including Artificial Intelligence (AI) for enhanced efficiency and accuracy. You will lead the testing efforts to identify and resolve issues, optimize performance, ensure cross-browser compatibility, and verify the scalability and resiliency of software capabilities under load. As part of our commitment to innovation, your role will involve implementing AI-powered testing methodologies to improve coverage and identify issues proactively. If you have hands-on experience with automation, cross-browser testing, performance testing, and industry-leading tools (including AI-based solutions), this is the perfect opportunity for your career growth. Key Responsibilities 1. Test Planning & Strategy Collaborate with product managers, developers, and other stakeholders to understand requirements and define test objectives. Develop and document comprehensive and efficient test plans, strategies, and exit criteria. Ensure alignment with Agile frameworks for CI/CD processes to maintain quality standards throughout the software development lifecycle. 2. Manual Testing Perform detailed manual testing on new features, functional flows, and regression cases. Conduct comprehensive exploratory testing for edge-case scenarios to uncover potential issues early. Ensure test data coverage for all features, workflows, integrations, and edge cases. 3. Automation Testing Design, build, and maintain automation frameworks for both web and mobile applications using leading tools like Selenium , Cypress , Playwright , and/or similar. Write efficient and reusable automated test scripts to conduct functional and end-to-end testing . Work on integrating automated tests into CI/CD pipelines (e.g., using Jenkins , GitHub Actions , AWS CodePipeline ). 4. Cross-Browser & Device Testing Perform cross-browser testing on modern browsers such as Chrome, Firefox, Safari, and Edge using tools like BrowserStack , Lambdatest , or CrossBrowserTesting . Validate software compatibility across various operating systems and devices (desktop and mobile). 5. Performance Testing Design and execute performance, scalability, and stress tests for high-traffic systems using tools like JMeter , LoadRunner , or Gatling . Monitor application response time, throughput, and behavior under heavy load scenarios. Analyze performance bottlenecks and provide optimization recommendations to development teams. 6. AI-Driven Testing Utilize AI-powered test case generation tools like Testim , Applitools , or Tricentis Tosca to design smarter and faster test cases. Work with AI-based tools for visual regression testing and intelligent defect identification. Stay up to date on emerging trends in AI-driven QA solutions to enhance testing strategies. 7. Defect Reporting & Debugging Identify, document, and track bugs and defects found during testing using bug-tracking tools such as JIRA , Trello , and Azure DevOps . Actively collaborate with development teams to troubleshoot and resolve defects, ensuring software efficiency and stability. 8. Documentation & Reporting Create and maintain a repository of detailed test plans, test cases, and test execution reports. Generate test metrics and quality reports to update stakeholders regarding system quality and testing progress. Requirements 1. Education & Experience Bachelor’s degree in Computer Science, Engineering, or a related field. 4–6 years of experience in a Software QA role, with a proven track record of delivering high-quality software products. 2. Technical Skills Strong understanding of software QA methodologies , manual and automation testing standards , and testing tools . Hands-on experience with manual  and automation testing of workflows and UI components. Proficiency with key automation testing frameworks (e.g., Selenium, TestNG, Playwright, Cypress, etc. ). Demonstrated expertise in cross-browser testing tools (e.g., BrowserStack, LambdaTest, Sauce Labs ). Advanced knowledge of performance and stress testing tools (e.g., JMeter, LoadRunner, Gatling, or k6 ). Experience with API testing tools such as Postman, Rest Assured , or Karate . Proficiency with test management tools (e.g., Jira, TestRail ) and version control systems like Git . Familiarity with CI/CD pipelines and DevOps tools (e.g., Jenkins, GitHub Actions, Azure Pipelines ). 3. AI Testing Tools Hands-on experience with AI-enhanced testing tools such as: Testim, Tricentis Tosca, Katalon AI, Applitools, and Mabl AI-powered visual testing and smart test case generation Understanding of AI-driven methodologies for predictive testing, defect prioritization, and anomaly detection. 4. Additional Skills Strong troubleshooting and debugging skills with an eye for detail. Excellent communication skills, with the ability to articulate complex issues to technical and business stakeholders clearly. Demonstrated ability to work in Agile environments and with techniques such as regression testing , exploratory testing, and smoke/sanity testing. Knowledge of scripting languages such as Python, JavaScript, or Java is a plus. Preferred Qualifications Certifications : ISTQB Foundation Level or Advanced Level certification Certified Selenium Professional, Appium Certification, or equivalent Experience in Performance & Load Testing : Hands-on knowledge with tools like JMeter or LoadRunner. Familiarity with AI/ML Testing : Experience testing machine-learning models or data-driven AI applications. Cloud Testing : Familiarity with testing APIs and services hosted on AWS , Azure , or GCP .

Location: Romania Job Overview We are seeking an experienced Software QA & Testing Engineer to join our dynamic team. In this role, you will play a crucial part in ensuring the delivery of high-quality software through robust manual and automated testing processes, as well as adopting modern testing tools including Artificial Intelligence (AI) for enhanced efficiency and accuracy. You will lead the testing efforts to identify and resolve issues, optimize performance, ensure cross-browser compatibility, and verify the scalability and resiliency of software capabilities under load. As part of our commitment to innovation, your role will involve implementing AI-powered testing methodologies to improve coverage and identify issues proactively. If you have hands-on experience with automation, cross-browser testing, performance testing, and industry-leading tools (including AI-based solutions), this is the perfect opportunity for your career growth. Key Responsibilities 1. Test Planning & Strategy Collaborate with product managers, developers, and other stakeholders to understand requirements and define test objectives. Develop and document comprehensive and efficient test plans, strategies, and exit criteria. Ensure alignment with Agile frameworks for CI/CD processes to maintain quality standards throughout the software development lifecycle. 2. Manual Testing Perform detailed manual testing on new features, functional flows, and regression cases. Conduct comprehensive exploratory testing for edge-case scenarios to uncover potential issues early. Ensure test data coverage for all features, workflows, integrations, and edge cases. 3. Automation Testing Design, build, and maintain automation frameworks for both web and mobile applications using leading tools like Selenium , Cypress , Playwright , and/or similar. Write efficient and reusable automated test scripts to conduct functional and end-to-end testing . Work on integrating automated tests into CI/CD pipelines (e.g., using Jenkins , GitHub Actions , AWS CodePipeline ). 4. Cross-Browser & Device Testing Perform cross-browser testing on modern browsers such as Chrome, Firefox, Safari, and Edge using tools like BrowserStack , Lambdatest , or CrossBrowserTesting . Validate software compatibility across various operating systems and devices (desktop and mobile). 5. Performance Testing Design and execute performance, scalability, and stress tests for high-traffic systems using tools like JMeter , LoadRunner , or Gatling . Monitor application response time, throughput, and behavior under heavy load scenarios. Analyze performance bottlenecks and provide optimization recommendations to development teams. 6. AI-Driven Testing Utilize AI-powered test case generation tools like Testim , Applitools , or Tricentis Tosca to design smarter and faster test cases. Work with AI-based tools for visual regression testing and intelligent defect identification. Stay up to date on emerging trends in AI-driven QA solutions to enhance testing strategies. 7. Defect Reporting & Debugging Identify, document, and track bugs and defects found during testing using bug-tracking tools such as JIRA , Trello , and Azure DevOps . Actively collaborate with development teams to troubleshoot and resolve defects, ensuring software efficiency and stability. 8. Documentation & Reporting Create and maintain a repository of detailed test plans, test cases, and test execution reports. Generate test metrics and quality reports to update stakeholders regarding system quality and testing progress. Requirements 1. Education & Experience Bachelor’s degree in Computer Science, Engineering, or a related field. 4–6 years of experience in a Software QA role, with a proven track record of delivering high-quality software products. 2. Technical Skills Strong understanding of software QA methodologies , manual and automation testing standards , and testing tools . Hands-on experience with manual  and automation testing of workflows and UI components. Proficiency with key automation testing frameworks (e.g., Selenium, TestNG, Playwright, Cypress, etc. ). Demonstrated expertise in cross-browser testing tools (e.g., BrowserStack, LambdaTest, Sauce Labs ). Advanced knowledge of performance and stress testing tools (e.g., JMeter, LoadRunner, Gatling, or k6 ). Experience with API testing tools such as Postman, Rest Assured , or Karate . Proficiency with test management tools (e.g., Jira, TestRail ) and version control systems like Git . Familiarity with CI/CD pipelines and DevOps tools (e.g., Jenkins, GitHub Actions, Azure Pipelines ). 3. AI Testing Tools Hands-on experience with AI-enhanced testing tools such as: Testim, Tricentis Tosca, Katalon AI, Applitools, and Mabl AI-powered visual testing and smart test case generation Understanding of AI-driven methodologies for predictive testing, defect prioritization, and anomaly detection. 4. Additional Skills Strong troubleshooting and debugging skills with an eye for detail. Excellent communication skills, with the ability to articulate complex issues to technical and business stakeholders clearly. Demonstrated ability to work in Agile environments and with techniques such as regression testing , exploratory testing, and smoke/sanity testing. Knowledge of scripting languages such as Python, JavaScript, or Java is a plus. Preferred Qualifications Certifications : ISTQB Foundation Level or Advanced Level certification Certified Selenium Professional, Appium Certification, or equivalent Experience in Performance & Load Testing : Hands-on knowledge with tools like JMeter or LoadRunner. Familiarity with AI/ML Testing : Experience testing machine-learning models or data-driven AI applications. Cloud Testing : Familiarity with testing APIs and services hosted on AWS , Azure , or GCP .

Location: Serbia Job Overview We are seeking an experienced Software QA & Testing Engineer to join our dynamic team. In this role, you will play a crucial part in ensuring the delivery of high-quality software through robust manual and automated testing processes, as well as adopting modern testing tools including Artificial Intelligence (AI) for enhanced efficiency and accuracy. You will lead the testing efforts to identify and resolve issues, optimize performance, ensure cross-browser compatibility, and verify the scalability and resiliency of software capabilities under load. As part of our commitment to innovation, your role will involve implementing AI-powered testing methodologies to improve coverage and identify issues proactively. If you have hands-on experience with automation, cross-browser testing, performance testing, and industry-leading tools (including AI-based solutions), this is the perfect opportunity for your career growth. Key Responsibilities 1. Test Planning & Strategy Collaborate with product managers, developers, and other stakeholders to understand requirements and define test objectives. Develop and document comprehensive and efficient test plans, strategies, and exit criteria. Ensure alignment with Agile frameworks for CI/CD processes to maintain quality standards throughout the software development lifecycle. 2. Manual Testing Perform detailed manual testing on new features, functional flows, and regression cases. Conduct comprehensive exploratory testing for edge-case scenarios to uncover potential issues early. Ensure test data coverage for all features, workflows, integrations, and edge cases. 3. Automation Testing Design, build, and maintain automation frameworks for both web and mobile applications using leading tools like Selenium , Cypress , Playwright , and/or similar. Write efficient and reusable automated test scripts to conduct functional and end-to-end testing . Work on integrating automated tests into CI/CD pipelines (e.g., using Jenkins , GitHub Actions , AWS CodePipeline ). 4. Cross-Browser & Device Testing Perform cross-browser testing on modern browsers such as Chrome, Firefox, Safari, and Edge using tools like BrowserStack , Lambdatest , or CrossBrowserTesting . Validate software compatibility across various operating systems and devices (desktop and mobile). 5. Performance Testing Design and execute performance, scalability, and stress tests for high-traffic systems using tools like JMeter , LoadRunner , or Gatling . Monitor application response time, throughput, and behavior under heavy load scenarios. Analyze performance bottlenecks and provide optimization recommendations to development teams. 6. AI-Driven Testing Utilize AI-powered test case generation tools like Testim , Applitools , or Tricentis Tosca to design smarter and faster test cases. Work with AI-based tools for visual regression testing and intelligent defect identification. Stay up to date on emerging trends in AI-driven QA solutions to enhance testing strategies. 7. Defect Reporting & Debugging Identify, document, and track bugs and defects found during testing using bug-tracking tools such as JIRA , Trello , and Azure DevOps . Actively collaborate with development teams to troubleshoot and resolve defects, ensuring software efficiency and stability. 8. Documentation & Reporting Create and maintain a repository of detailed test plans, test cases, and test execution reports. Generate test metrics and quality reports to update stakeholders regarding system quality and testing progress. Requirements 1. Education & Experience Bachelor’s degree in Computer Science, Engineering, or a related field. 4–6 years of experience in a Software QA role, with a proven track record of delivering high-quality software products. 2. Technical Skills Strong understanding of software QA methodologies , manual and automation testing standards , and testing tools . Hands-on experience with manual  and automation testing of workflows and UI components. Proficiency with key automation testing frameworks (e.g., Selenium, TestNG, Playwright, Cypress, etc. ). Demonstrated expertise in cross-browser testing tools (e.g., BrowserStack, LambdaTest, Sauce Labs ). Advanced knowledge of performance and stress testing tools (e.g., JMeter, LoadRunner, Gatling, or k6 ). Experience with API testing tools such as Postman, Rest Assured , or Karate . Proficiency with test management tools (e.g., Jira, TestRail ) and version control systems like Git . Familiarity with CI/CD pipelines and DevOps tools (e.g., Jenkins, GitHub Actions, Azure Pipelines ). 3. AI Testing Tools Hands-on experience with AI-enhanced testing tools such as: Testim, Tricentis Tosca, Katalon AI, Applitools, and Mabl AI-powered visual testing and smart test case generation Understanding of AI-driven methodologies for predictive testing, defect prioritization, and anomaly detection. 4. Additional Skills Strong troubleshooting and debugging skills with an eye for detail. Excellent communication skills, with the ability to articulate complex issues to technical and business stakeholders clearly. Demonstrated ability to work in Agile environments and with techniques such as regression testing , exploratory testing, and smoke/sanity testing. Knowledge of scripting languages such as Python, JavaScript, or Java is a plus. Preferred Qualifications Certifications : ISTQB Foundation Level or Advanced Level certification Certified Selenium Professional, Appium Certification, or equivalent Experience in Performance & Load Testing : Hands-on knowledge with tools like JMeter or LoadRunner. Familiarity with AI/ML Testing : Experience testing machine-learning models or data-driven AI applications. Cloud Testing : Familiarity with testing APIs and services hosted on AWS , Azure , or GCP .

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We build and run the secure execution environment behind Claude's agentic capabilities. When Claude writes and runs code, browses the web, or uses a computer, that happens on infrastructure our team owns. We work at the intersection of systems engineering and security. The goal is to make untrusted code execution safe, fast, and reliable enough that product teams don't have to think about it. This is the layer between the model and the outside world, and it has to hold up at scale for every Anthropic product. We're hiring engineers who have experience building for containerized workloads and have a keen eye for building products used by millions of customers. What you'll do You'll independently scope complex, multi-month projects, drive cross-org alignment through ambiguous problem spaces, and make architectural decisions that shape how Anthropic builds and scales its products. You'll partner directly with research to productize cutting-edge capabilities, and will have lasting impact on the platform that hundreds of thousands of companies and internal/external engineers depend on every day. You might be a good fit if you: Have a minimum of 8 years of practical experience as a backend or platform engineer building scalable distributed systems, ideally operating at tech lead level or equivalent distributed systems, cloud-native products, developer tools, or external developer facing products Have strong fundamentals in service-oriented architectures, networking, and systems design, ideally having owned both the technical vision and execution of a foundational platform system end to end Are proficient in Python, Go, Rust, or similar systems languages Have experience with cloud infrastructure (GCP, AWS, or Azure), container orchestration (Kubernetes), and/or multi-cloud networking Take full ownership of your work—from design through deployment and operations Can navigate ambiguity and make sound technical decisions independently, and have ideally operated in 0 to 1 and more mature team or company settings Take a product-focused approach to platform work and care about building solutions that are robust, scalable, and easy to us Deadline to apply: None. Applications will be reviewed on a rolling basis. Location Preference: Preference will be given to candidates based in NY, SEA, SF or the Bay Area given the current location of team. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: United Kingdom; Poland; Germany; Romania; Netherlands; Spain Location: Europe (100% Remote) Contract Type: Advisory / Project-Based About Us Where elite tech talent meets world-class opportunities! At Xenon7, we work with leading enterprise clients and innovative startups on high-impact projects across Data, AI, Cloud, and Software Engineering. Our expertise in AI solution architecture and specialized technical talent allows us to partner with enterprise leaders on transformative initiatives, driving innovation and business growth. Job Summary We are seeking an Agentforce AI Maestro to join our elite European advisory roster under Xenon7's flexible Maestro Model. This strategic, fractional role combines enterprise Salesforce architecture with advanced LLM engineering to lead high-level technical discovery, design agentic workflows, and oversee production deployments for enterprise clients across Europe. Rather than a standard full-time commitment, this role provides high-leverage advisory engagements and project-based execution, with the potential to evolve into a full-time principal position as engagements scale. This is a hands-on technical lead role, not a Salesforce admin position. A. Agentforce Architecture & System Design Solution Architecture: Translate complex enterprise business processes into end-to-end agentic workflows (Intent $\rightarrow$ Agent $\rightarrow$ Context $\rightarrow$ Reasoning $\rightarrow$ Actions $\rightarrow$ Systems $\rightarrow$ Outcome). Core Agent Engineering: Design, configure, and build enterprise agents using Agent Builder, Agentforce Studio, Agent Script / DX, subagent routing, and instructions. Deterministic Logic Integration: Build robust back-end support using Salesforce Flow, Apex, SOQL, APIs, Named Credentials, and OAuth. B. Agentic AI & LLM Engineering Orchestration & Tooling: Implement tool/function calling, structured outputs, multi-step agent workflows, and prompt/context engineering. Architectural Trade-offs: Evaluate and determine when to leverage LLM reasoning versus deterministic Apex/Flow logic to minimize latency and token costs while preventing hallucinations. C. Enterprise Data & System Integration Grounding & RAG: Ground agent reasoning in structured/unstructured enterprise data utilizing Salesforce Data Cloud / Data 360, semantic search, and Knowledge libraries. System Interoperability: Architect REST API callouts, event-driven integrations, and MuleSoft platform pipelines, incorporating Model Context Protocol (MCP) standards. D. Testing, Security & Strategic Advisory Testing & Quality Assurance: Drive automated testing and multi-turn conversation tracing using the Agentforce Testing Center. Security & Guardrails: Design least-privilege agent permissions, FLS/sharing rules, prompt injection protections, and human-in-the-loop escalation paths. Client & Team Leadership: Lead technical discovery with European enterprise stakeholders and guide cross-functional engineering teams. Requirements Experience: 5+ years of hands-on Salesforce engineering and architecture experience. Agentforce Track Record: At least 2 meaningful production or advanced pre-production Agentforce implementations. Location: Based in Europe with strong alignment with European enterprise hours. Core Tech Stack: Deep proficiency in Salesforce Agentforce (Studio/DX), Apex, Flow, Data Cloud, REST APIs, Git, and CI/CD pipelines. AI Competency: Clear understanding of LLM architectures, context window management, function calling, and evaluation frameworks. Preferred Certifications & Qualifications Salesforce Certified Agentforce Specialist or Salesforce Architect Certifications. Hands-on experience with MuleSoft, Python, TypeScript, LangGraph/LangChain, or MCP. Exposure to major AI platforms (OpenAI, Anthropic, Gemini, Azure AI, or AWS Bedrock)

Location: Dammam, Saudi Arabia The Enterprise Computing & Cloud Architect is responsible for defining and governing the enterprise architecture for computing and infrastructure platforms across on-premises environments, private cloud, public cloud, and High-Performance Computing (HPC) and AI infrastructure. Key Responsibilities Own and maintain the enterprise architecture for computing platforms across on-premises, private cloud, public cloud, HPC, and AI environments. Define enterprise target architectures, reference architectures, technology standards, principles, and design patterns for computing and cloud platforms. Develop and maintain strategic technology roadmaps aligned with business objectives, enterprise architecture strategy, and emerging technology trends. Provide architecture leadership and assurance for major programs, transformation initiatives, and complex technology solutions. Evaluate and recommend infrastructure, cloud, computing, virtualization, containerization, HPC, and AI technologies based on enterprise requirements. Establish architectural principles and standards covering scalability, availability, performance, security, resilience, interoperability, and cost optimization. Ensure alignment between solution architectures and the enterprise architecture, technology standards, and strategic direction. Lead architecture reviews and provide technical governance throughout the solution lifecycle. Assess current-state environments and develop transition architectures and migration strategies toward the target state. Define cloud adoption, hybrid cloud, workload placement, and infrastructure modernization strategies. Collaborate with cybersecurity, data, applications, networking, operations, and other architecture domains to ensure integrated enterprise solutions. Provide architectural guidance for high-performance and AI computing platforms, including compute capacity, acceleration technologies, scalability, and integration requirements. Assess technology risks, technical debt, architectural dependencies, and opportunities for modernization. Required Qualifications & Experience Bachelor’s degree in Computer Engineering, Computer Science, Information Technology, or a related discipline. Master’s degree in a relevant field is preferred. 10+ years of experience in technology, infrastructure, cloud, or enterprise architecture , with significant experience in large-scale enterprise environments. Demonstrated experience designing and governing complex computing and infrastructure platforms. Strong experience across on-premises infrastructure and public/private cloud environments. Experience with HPC and/or AI infrastructure architecture is highly desirable. Strong understanding of cloud architecture, virtualization, containers, compute platforms, storage, networking, and infrastructure automation. Experience developing enterprise architecture standards, reference architectures, technology roadmaps, and governance frameworks. Proven experience providing architectural assurance for major programs and complex technology implementations. Strong understanding of security, resilience, availability, scalability, performance, and infrastructure cost optimization principles. Excellent stakeholder management, communication, analytical, and problem-solving skills. Preferred Certifications Relevant architecture, cloud, or technology certifications such as: TOGAF or equivalent enterprise architecture certification. AWS, Microsoft Azure, or Google Cloud architecture certifications. Relevant VMware, Kubernetes, HPC, AI infrastructure, or other specialist technology certifications. Key Competencies Enterprise & Technology Architecture Cloud & Hybrid Cloud Architecture Computing & Infrastructure Architecture HPC & AI Infrastructure Architecture Governance & Assurance Technology Strategy & Roadmapping Solution Evaluation & Design Technology Risk Management Stakeholder & Vendor Management Strategic Thinking and Innovation

Location: Oakland, California, United States, AMER From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven. About Us Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on. Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions. As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact. ​ During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites. About the Role Fivetran + dbt is building data pipelines to power the modern data stack for thousands of companies. We’re looking for a high-performance, experienced hands-on technical program manager(TPM) in the security domain to be part of an Engineering team. In this role, you will be responsible for leading and managing security-related initiatives across the organization. It involves collaborating with cross-functional teams to ensure the successful planning, execution, and delivery of security programs. The TPM will act as a bridge between technical teams and business stakeholders, ensuring alignment with organizational goals while mitigating security risks. The work is very diverse. Fivetran is a multi-cloud environment operating on AWS, GCP, and Azure. You will help select security tools, implement improvements within our environments, and assist in developing new processes to increase our security posture. This is a full-time position based out of our Oakland, CA office. Our hybrid work model offers a blend of remote flexibility and in-person collaboration, including two days in the office each week to connect and build as a team. Technologies You’ll Use Bash, Python, JS, BigQuery, Looker, Sigma, Azure, AWS, GCP, Terraform, Docker, Kubernetes, Github, Buildkite, SonarQube, Grafana, Prisma, Synk, Signal Sciences, AI Tools What You’ll Do This is the primary person in engineering responsible for executing the security vulnerability management program for engineering, including infrastructure, code, and dependency vulnerabilities. Collaborate with Security and Engineering teams to ensure vulnerabilities are identified, prioritized, and patched. Provide technical oversight and accountability to ensure the effective delivery of security fixes. Enhance processes by evaluating tools, recommending improvements, and driving automation for faster resolution. Usage of AI in defining the roadmap for a proactive security approach based on risk assessment/rating Running the Dependency management and image hardening programs Using AI to contribute to the remediation of code and infrastructure vulnerabilities Establish and lead a code scanning program in collaboration with infrastructure, engineering, and security teams to ensure seamless integration and sustainable security practices. Dedicate up to 20% of the time to assessing business systems to identify vulnerabilities and compliance gaps proactively. Develop a scanning and detection plan and establish policies and standards for internal data access tools to improve overall system security. Advocate for tools and solutions that support shift-left strategies, driving early integration of security and testing in the development lifecycle. Skills We’re Looking For Over 5 years of experience in technical program management with a strong focus on security engineering, vulnerability management, cloud security, and application security. Proficient in applying program management methodologies, tools, and best practices to deliver complex security initiatives. Exceptional skills in prioritization, organization, and multitasking to manage multiple programs effectively. Proven ability to work collaboratively with cross-functional teams, including product teams, SRE/QE engineers, and developers, to embed a security-first mindset into workflows and practices. Deep understanding of key security domains, including application/infrastructure security, data privacy, threat modeling, vulnerability management, and secure software development lifecycle (SDLC). Strong grasp of security concepts and principles, including network security, encryption, authentication, and authorization. Hands-on experience with SAST/DAST tools, agent-based firewalls, IDS/IPS technologies, and automation tools for security orchestration. Experience with scripting languages for automating security processes. Proficient in researching and validating vulnerabilities while proposing effective remediation or mitigation strategies. Strong familiarity with OWASP principles and best practices for securing web applications, including the OWASP Top 10 vulnerabilities and Application Security Verification Standard (ASVS) Up-to-date knowledge of market trends, emerging technologies, and best practices in cloud security Strong analytical, problem-solving, and communication skills to address security challenges, coupled with the ability to influence and collaborate effectively with engineering teams in enhancing security measures and mitigating vulnerabilities in a dynamic, fast-paced environment. #LI-HYBRID #LI-EM1 The compensation range displayed on this job posting reflects the minimum and maximum target for new hire compensation for the target position and level, and may include sales incentives or target bonuses depending on the role.  Our compensation ranges are determined by role, level, and location. Our job titles may span more than one career level. Within the range, individual compensation is determined by additional factors, including job-related skills, experience, relevant education or training, business need, market demands. The compensation range is subject to change and may be modified in the future. Your recruiter can share more about the specific compensation range for your location during the hiring process. Oakland Pay Range $158,284 — $197,855 USD Perks and Benefits 100% employer-paid medical insurance * Generous paid time away from work, including paid vacation or flexible/unlimited vacation depending on role and country, plus paid sick time, inclusive parental leave, paid holidays, including a year-end Global Week of Rest, and volunteer days off. RSU stock grants* Professional development and training opportunities Company virtual happy hours, free food, and fun team-building activities Monthly cell phone stipend Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self-guided mindfulness exercises for all covered employees and their covered dependents. * May vary by country and worker type - please reach out to your recruiter for more information Click here to learn more about Fivetran's Benefits by Region. We’re honored to be valued at over $5.6 billion , but more importantly, we’re proud of our core values of Get Stuck In, Do the Right Thing, and One Team, One Dream . Read about us in Forbes . Fivetran brings together high-quality talent across the globe to make data access as easy and reliable as electricity for our customers. We value and recognize that our customers benefit from having innovative teams made of people from many backgrounds, experiences, and identities. Fivetran promotes diversity, equity, inclusion & belonging through attracting, recruiting, developing, and retaining a diverse workforce, not only because it is the right thing to do, but because it helps us build a world-class company to better serve our customers, our people and our communities. To learn more about Fivetran’s culture and what it’s like to be part of the team, click here and enjoy our video. To learn more about our candidate privacy policy, you can read our statement here . We are committed to ensuring that all candidates have an equal opportunity to participate in our interview process. If you require accommodations at any stage of the process due to a disability, medical condition, or any other circumstance, please don't hesitate to submit your request by filling out this form . We will work with you to provide reasonable accommodations to facilitate your participation and ensure a fair and accessible interview experience. Your request and any information provided will be kept confidential and will not impact your candidacy. We look forward to hearing from you and accommodating your needs to the best of our ability.

Location: United States (Remote) Workplace: Remote SUMMARY We are seeking a Staff Software Engineer to join our Traffic team https://temporalio.notion.site/Join-the-Traffic-Team-at-Temporal-2e98fc56773880f3b8f5f5d35f23d82a, where you will play a key role in driving the technical strategy, execution, and leadership of projects across traffic management, network optimization, and cloud orchestration. This is an exciting opportunity to significantly impact the scalability, reliability, and operational excellence of Temporal’s networking infrastructure, while also mentoring and guiding the team. WHAT YOU'LL DO Invent - Lead the design and development of systems that optimize network traffic and scale for global expansion. - Drive architectural decisions for high-impact projects, ensuring scalability and reliability. - Co-author long-term technical roadmaps that set the vision for network scalability, performance, and engineering velocity. - Set the standard for a culture of engineering and operational excellence. Own - Build and nurture effective partnerships across engineering, product, and security teams to align on network infrastructure goals. - Lead and conduct design reviews for critical projects with a focus on system-level tradeoffs and network scalability. - Drive the design and implementation of “secure by default” network systems in collaboration with security teams. - Act as a key stakeholder by engaging with customers and internal teams to understand business requirements and deliver innovative solutions. Learn - Deeply understand how to leverage Temporal’s software to build and scale networking infrastructure. - Gather insights into customer needs and incorporate them into technical decision-making for traffic management and networking strategies. - Stay at the forefront of technology advancements in traffic management, networking, and cloud orchestration. Collaborate - Mentor and guide engineers, sharing best practices and design principles for building reliable and scalable networking systems. - Drive alignment across teams, ensuring roadmaps are cohesive and deliverables are on track. - Foster a collaborative and growth-oriented environment, helping others improve while continuing to expand your own expertise. WHAT YOU'LL BRING - Proven experience leading complex engineering efforts focused on network traffic management, network optimization, and cloud orchestration. - Exceptional collaboration and communication skills, with a demonstrated ability to align stakeholders and lead cross-functional teams. - A track record of contributing to long-term technical roadmaps and making thoughtful system-level tradeoffs. - At least 8+ years of coding experience in languages like Go, Java, or similar, with strong expertise in writing concurrent and distributed code. - Extensive experience designing and building distributed systems, leveraging concurrency primitives, and optimizing network performance. - Deep expertise in traffic and networking systems, with familiarity across adjacent infrastructure domains. - Hands-on experience with cloud providers such as AWS, GCP, or Azure, and the ability to optimize cost, performance, and scalability. - Operational experience with Envoy and xDS configuration. Bonus for custom controller expertise and controller migration familiarity. - A strong sense of ownership and the ability to balance short-term priorities with long-term strategic goals.. Temporal Technologies is an Equal Opportunity Employer. Temporal Technologies does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status, or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need. We embrace and celebrate differences and diversity. Temporal is committed to providing access, equal opportunity, and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. If you need to request a reasonable accommodation, please let your Recruiter know so we can assist.

Location: United States (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. Staff Backend Engineer - Mimir Query, Databases This is a remote position. We are looking for candidates in the USA time zones. What is Grafana Cloud? Grafana Cloud is our composable observability platform that integrates metrics, logs, traces, and profiles with Grafana. It allows our customers to leverage the best open source observability software – including Prometheus, Mimir, Loki, Tempo, and Pyroscope – without the overhead of installing, maintaining and scaling their own observability stack. The Databases team owns and operates the telemetry databases that are Mimir for metrics , Loki for logs , Tempo for traces , and Pyroscope for profiles . Our databases are offered as a hosted service in Grafana Cloud, and additionally as on-premise solutions with Grafana Enterprise Metrics , Grafana Enterprise Logs , and Grafana Enterprise Traces . They are multi-tenant distributed systems implemented in Go and operating at scale on Kubernetes across all major Cloud service providers (AWS, GCP, Azure). As a company we are remote-first and global, we embrace people of different experiences and backgrounds to build diverse teams where every person brings a new perspective to the software. Mimir Squad The Mimir squad has 3 sub-squads, Ingest, Storage, and Query, which together maintain the Mimir OSS project , and additionally own and operate Grafana Cloud Metrics across 3 major cloud providers. Engineers on the team focus on optimizing the efficiency and resilience of processing, storing, and querying metrics at large volumes. These services operate at a large scale and performance is key to keeping the offering competitive and running smoothly. A Mimir engineer has various work streams. They are likely engaged in a larger project with another engineer, and they are also incorporating some performance and reliability improvements discovered through operating the system in production. They are also responsible for writing and reviewing PRs and design documents from other engineers in the squad, shepherding automated release rollouts, and participating in the on-call rotation for their systems. What will you be doing: Take an active role in influencing our roadmap and your own career objectives Work with your team to deliver new features, then use the results to iterate and improve. Drive projects from initial idea all the way to operations once it is in the hands of customers Embrace our open-source culture and contribute to other projects that may not directly fall within your team’s scope Design, build, operate, and maintain critical systems, owning the reliability, performance, and availability Be a part of your team’s follow-the-sun on-call rotations and take ownership of the services you’re running Support other team members, participate in design discussions and collaborate with the team Learn new skills by gaining a deeper understanding of our cloud product and our customers and getting to know the codebase of a large distributed system We invest heavily in developer productivity. You can use modern AI coding assistants as part of your daily workflow (your choice of tools, within security guidelines), backed by a company-funded usage budget so you can iterate quickly without unnecessary friction. We encourage pragmatic AI-assisted development: faster prototyping, test generation, refactors, documentation, and incident follow-ups—always with strong code review and quality standards. You'll also have access to the latest frontier models from OpenAI, Anthropic, and Google. What makes you a great fit: You are a motivated self starter with a bias towards action. You are customer focused. We build everything with our users in mind. You have a passion for creating intuitive products that fit customers’ needs. You have good time management skills, which you leverage to work on the right things at the right time. Pragmatism: You are able to take on complex challenges and break them down to achieve short feedback loops: to analyze, design, and build modular solutions, deliver MVPs, gather data and feedback and then progress iteratively Collaboration and communication: The smallest unit we have is a squad. You’ll be working with your teammates in a fully remote setup. Good communication and time management skills are a must. Solid experience with at least one programming language. We use Go, but if you have familiarity with Python, C, C++, Rust or similar then that translates well Experience with leading and delivering projects from gathering requirements, brainstorming ideas all the way to shipping a product to the customer’s hands in a self-driven and collaborative way Experience with developing software that runs in the Cloud or experience with systems engineering Experience with being on-call and following the DevOps model Experience writing clean, robust, and performant software that is easily maintained by others Familiarity with observability systems, know when to use metrics, logs, traces, to debug a problem. Comfortable with microservices architecture and distributed systems Experience and comfort developing with LLMs like Claude and Codex on your day to day Bonus Points For: Experience working with Kubernetes Experience working with queue systems, e.g. the Kafka protocol Been a user of Grafana and Prometheus in operational roles (including on-call for your team at a previous employer or just using these tools on hobby/homelab projects) Familiarity with the concept of infrastructure as code Compensation & Rewards: In the United States, the Base compensation range for this role is USD 189,374 - USD 227,249 .  Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits include equity, bonus (if applicable) and other benefits listed here . *Compensation ranges are country-specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Location: Canada (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. Staff Backend Engineer - Mimir Query, Databases This is a remote position. We are looking for candidates in Canadian time zones. What is Grafana Cloud? Grafana Cloud is our composable observability platform that integrates metrics, logs, traces, and profiles with Grafana. It allows our customers to leverage the best open source observability software – including Prometheus, Mimir, Loki, Tempo, and Pyroscope – without the overhead of installing, maintaining and scaling their own observability stack. The Databases team owns and operates the telemetry databases that are Mimir for metrics , Loki for logs , Tempo for traces , and Pyroscope for profiles . Our databases are offered as a hosted service in Grafana Cloud, and additionally as on-premise solutions with Grafana Enterprise Metrics , Grafana Enterprise Logs , and Grafana Enterprise Traces . They are multi-tenant distributed systems implemented in Go and operating at scale on Kubernetes across all major Cloud service providers (AWS, GCP, Azure). As a company we are remote-first and global, we embrace people of different experiences and backgrounds to build diverse teams where every person brings a new perspective to the software. Mimir Squad The Mimir squad has 3 sub-squads, Ingest, Storage, and Query, which together maintain the Mimir OSS project , and additionally own and operate Grafana Cloud Metrics across 3 major cloud providers. Engineers on the team focus on optimizing the efficiency and resilience of processing, storing, and querying metrics at large volumes. These services operate at a large scale and performance is key to keeping the offering competitive and running smoothly. A Mimir engineer has various work streams. They are likely engaged in a larger project with another engineer, and they are also incorporating some performance and reliability improvements discovered through operating the system in production. They are also responsible for writing and reviewing PRs and design documents from other engineers in the squad, shepherding automated release rollouts, and participating in the on-call rotation for their systems. What will you be doing: Take an active role in influencing our roadmap and your own career objectives Work with your team to deliver new features, then use the results to iterate and improve. Drive projects from initial idea all the way to operations once it is in the hands of customers Embrace our open-source culture and contribute to other projects that may not directly fall within your team’s scope Design, build, operate, and maintain critical systems, owning the reliability, performance, and availability Be a part of your team’s follow-the-sun on-call rotations and take ownership of the services you’re running Support other team members, participate in design discussions and collaborate with the team Learn new skills by gaining a deeper understanding of our cloud product and our customers and getting to know the codebase of a large distributed system We invest heavily in developer productivity. You can use modern AI coding assistants as part of your daily workflow (your choice of tools, within security guidelines), backed by a company-funded usage budget so you can iterate quickly without unnecessary friction. We encourage pragmatic AI-assisted development: faster prototyping, test generation, refactors, documentation, and incident follow-ups—always with strong code review and quality standards. You'll also have access to the latest frontier models from OpenAI, Anthropic, and Google. What makes you a great fit: You are a motivated self starter with a bias towards action. You are customer focused. We build everything with our users in mind. You have a passion for creating intuitive products that fit customers’ needs. You have good time management skills, which you leverage to work on the right things at the right time. Pragmatism: You are able to take on complex challenges and break them down to achieve short feedback loops: to analyze, design, and build modular solutions, deliver MVPs, gather data and feedback and then progress iteratively Collaboration and communication: The smallest unit we have is a squad. You’ll be working with your teammates in a fully remote setup. Good communication and time management skills are a must. Solid experience with at least one programming language. We use Go, but if you have familiarity with Python, C, C++, Rust or similar then that translates well Experience with leading and delivering projects from gathering requirements, brainstorming ideas all the way to shipping a product to the customer’s hands in a self-driven and collaborative way Experience with developing software that runs in the Cloud or experience with systems engineering Experience with being on-call and following the DevOps model Experience writing clean, robust, and performant software that is easily maintained by others Familiarity with observability systems, know when to use metrics, logs, traces, to debug a problem. Comfortable with microservices architecture and distributed systems Experience and comfort developing with LLMs like Claude and Codex on your day to day Bonus Points For: Experience working with Kubernetes Experience working with queue systems, e.g. the Kafka protocol Been a user of Grafana and Prometheus in operational roles (including on-call for your team at a previous employer or just using these tools on hobby/homelab projects) Familiarity with the concept of infrastructure as code Compensation & Rewards: In Canada, the Base compensation range for this role is CAD 192,891 - CAD 231,469 .  Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits include equity, bonus (if applicable) and other benefits listed here . Compensation ranges are country-specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. *Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .