Powder Coater Jobs

We're looking for a Senior Infrastructure Engineer who brings strong software engineering skills and a deep understanding of production systems. This role is a good fit for someone who enjoys building systems that make infrastructure more scalable, reliable, and easy to operate – using code, not runbooks. You'll work with a highly collaborative team to design and build the internal platforms that power all of Asana, from product features to AI systems to offline analytics. Our tech stack includes: AWS, Kubernetes (EKS), MySQL (RDS), OpenSearch, DynamoDB, Redis, Terraform, Datadog, TypeScript, Scala, Go, and Python. We’re especially interested in people who think like backend engineers but care deeply about systems – things like failure modes, operational cost, debuggability, and performance. This role is based in our Warsaw office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do, and your recruiter can share more about the in-office requirements. We offer a Contract of Employment (UoP) for our employees in Poland. What you’ll achieve: Design and build frameworks, tools, and services that improve the reliability, observability, and scalability of Asana’s infrastructure. Lead end-to-end projects, from scoping and design through to rollout, across multiple systems and teams. Improve the operability of stateful infrastructure like MySQL, OpenSearch, and DynamoDB – and help drive Asana’s long-term vision for storage reliability. Debug production issues across the stack. Yes, there’s an on-call rotation – but this isn’t a pager monkey role. You’re here to fix things properly and make sure they don’t break again. Partner with product teams to shape a service-oriented architecture that enables fast, reliable development. Share knowledge through code reviews, design discussions, and mentorship. Abou

The Infrastructure team builds the foundation we need to support our web and mobile applications, as well as our robust API. We build and operate the software that enables Asana's security, scalability, and speed. Each day, we combine industry best-practices and innovation to support this product-focused company. We're looking for a Junior Infrastructure Software Engineer (New Grad) with a growing passion for Site Reliability and Operability. You will work with a world-class team of engineers on deploying and operating existing systems, and building new ones for challenges that are unique to our problem space. You will have a unique opportunity to learn how to design, develop, and operate services that power Asana, working on projects that help define the future of our infrastructure and how we architect and operate critical services at scale. This role is based in our Reykjavik office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. What You’ll Achieve Learn and Execute: Experience growth and development by being paired with a mentor who will support and guide you through opportunities to stretch and learn. Engineering Craftsmanship: Participate in Asana’s robust technical boot camps to learn our standards for high-quality, maintainable code. You will eventually own specific technical domains through our Areas of Responsibility (AoR) system. Build Foundations: Contribute to projects that define the future of infrastructure for Asana, learning how we architect and operate critical services at scale. Global Collaboration: Partner with other infrastructure teams in San Francisco, New York, and Warsaw to understand and contribute to our service-oriented architecture while navigating cross-timezone workflows. Tooling & Frameworks: Help develop framework

Datadog is entering a new chapter in how our product looks, feels, and operates. Our Design Lab is defining a new visual direction for the platform, and we’re looking for a Senior Staff Visual Product Designer to help turn that direction into a coherent product experience. Datadog is dense, technical, and used by people working through complex problems—often under real pressure. The challenge is not simply applying a new aesthetic. It is rethinking hierarchy, layout, navigation, interaction, and product patterns so the experience becomes clearer, more cohesive, and more expressive without losing the power our users rely on. This is a hands-on product design leadership role for someone who combines strong visual judgment with deep product and systems thinking. You’ll work alongside visual designers, motion designers, product designers, Design Systems, and Engineering to ensure the new direction changes how Datadog works—not just how it looks. What You'll Do Co-develop Datadog’s next visual direction by applying and stress-testing it across representative product journeys. Translate visual principles into concrete decisions about hierarchy, layout, navigation, information architecture, interaction, and behavior. Use visual language to clarify complex, data-dense experiences — hierarchy, density, and attention. Hold the visual quality bar across work you don't own, and align teams around it. Prototype, test, and refine new patterns before they become systemized. Partner deeply with Product Design, Design Systems, and engineering to turn successful concepts into durable system guidance and implementation. Create clear artifacts, pilots, and narratives that help teams adopt the direction and raise the product quality bar. Influence stakeholders across design, engineering, product, and executive partners. You will report directly to the Design Director and work as part of a small, focused team defining the future state before it scales across hundreds

At Datadog, we don’t just support our products, we master them. As Datadog’s in-house product experts, the Technical Escalation Engineering (TEE) team plays a critical role in driving our global success. We enable our customers, from the world’s most innovative startups to the largest enterprises, to harness the full power of Datadog’s platform, ensuring their growth, reliability, and performance. Through deep technical expertise, relentless problem-solving, and exceptional customer engagement, we educate, guide, and troubleshoot, delivering high-impact solutions that shape the customer experience. Whether through hands-on technical call, in-depth fact findings meeting, or complex investigations, we set the gold standard for technical excellence and customer advocacy. As part of our TEE team, you’ll tackle the most challenging technical problems, collaborate directly with Engineering and Product to refine and evolve our platform, and mentor teams worldwide, elevating the technical bar at every level. This is not just a support role; this is a career-defining opportunity to push boundaries, grow as an expert, and make a tangible impact on both our customers and Datadog’s future. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Manage, develop, coach and mentor Technical Escalation Engineers and/or people managers and their teams who respond to client requests, reproduce and troubleshoot issues, and dive into Datadog’s 400+ integrations Partner with Technical Engineering Director colleagues and VP of Support Engineering on strategic, global initiatives at scale Ensure the successful onboarding and development of Technical Escalation Engineers Oversee all projects and initiatives within the region, as well as cross regional ones, and functional a

The Behavior AI team builds the AI-based anomaly detection behind Datadog's security products. Our models learn what normal looks like across the billions of logs, events, and telemetry records flowing through the platform every second, and they flag the behavior that does not fit, on every record, in real time, at a cost that makes sense at our scale. What we build does not ship to a single feature. The same models power detection across many of Datadog's security products at once, so the work has impact well beyond any one team. Large general-purpose models are too slow and too expensive to run in that path, so we take the opposite approach: small, custom models, designed for high-throughput stream processing and optimized to run cheaply on every record. We are hiring a Senior Applied Scientist to build these models from start to finish. You will contribute to designing the architecture, training at scale, and the optimization work that takes a model from training to running efficiently on production traffic. This optimization requires a deep understanding of the constraints imposed by both the software and the hardware, together with the applied mathematics to work within them: often it comes down to finding a mathematical reformulation that fits those constraints better, and that judgment can decide whether a model reaches production at all. The work involves a number of open questions. How do you obtain most of the quality of a large model from one that is far smaller and cheap enough to run on the full stream? Where is it worth trading exactness for speed, and how do you reason about the error you accept? How do you make a small model's outputs clear enough that the detection engineers and analysts who rely on it can trust what it reports? If these are the problems you want to work on, we would like to hear from you. At Datadog, we place value in our office culture: the relationships and collaboration it builds, and the creativity it bring

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r

The Storage Layer Services team is currently re-architecting the MongoDB Cloud Storage Layer. This is a relatively new team in MongoDB that sits at the heart of the next generation MongoDB Cloud Storage Architecture, and the team is working to build performant multi-tenant distributed storage services both to enhance our existing MongoDB cloud storage architecture and to power more of our customers' use cases more efficiently. Engineering at MongoDB is globally distributed, with a mix of folks being fully remote, hybrid, or in-office. We have a small but growing team that calls Sydney home, and we are looking for a Staff Engineer to join the team working closely with other teams in Sydney and North America. Our team champions a strong culture of inclusivity, diversity, and collaboration. If you want to work on a collaborative team that applies great engineering fundamentals to deliver core features of a popular database, join us! Let’s change what’s possible for application developers, system architects, and database operators. We are looking to speak to candidates who are based in Sydney for our hybrid working model. You’re an ideal candidate if: You have 10+ years of experience in programming, debugging, and performance tuning highly concurrent and/or distributed systems. Especially if you have worked in a systems language (C, C++, Rust, etc) for a number of those years You have a track record as an effective technical leader. You love helping teams be successful at solving vaguely defined problems in iterative and measurable ways. You put the customer first, and don’t hesitate to cross team boundaries in search of the right solution You have a solid grasp of related systems fundamentals, such as cache management, log-based recovery, transactions or performance profiling You’re comfortable reasoning about highly concurrent, asynchronous services — backpressure, tail latency, and the failure modes of replicated state machines You’ve worked on large, highly availabl

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r

We are looking to speak to candidates who are based in Gurugram for our hybrid working model. About the Role We are looking for a Staff Integration Engineer (Workato & API Integration) to join our GTMTech team. This strategic role will lead the design, implementation, and governance of enterprise-grade integrations that power our core business processes across GTM systems, with a primary focus on Workato-based integrations and modern API management patterns. You will own the architecture for critical integration domains such as Quote-to-Cash and other high-impact GTMTech programs, ensuring our integration landscape is scalable, secure, observable, and aligned with best practices for event-driven and API-first designs. You will partner with engineering, architecture, security, and business stakeholders to define standards, mentor other integration engineers, and drive continuous improvement in how we connect systems and data. The GTMTech team is focused on high-impact, large-scale technology programs, such as Quote-to-Cash. Our mission is to enhance company efficiency, boost profitability, and enable data-driven decision-making by streamlining systems, optimizing processes, and minimizing manual, low-value work through automation and AI. Key Responsibilities Lead the end-to-end architecture, design, and implementation of Workato-based integrations and APIs across GTM systems (e.g., Salesforce, NetSuite, HRIS, Google Workspace) with a focus on scalability, reliability, and security Define and evolve integration standards, patterns, and best practices, including canonical integration patterns, error-handling strategies, observability, and operational runbooks Design and review complex, event-driven integration workflows leveraging technologies such as Kafka or equivalent messaging platforms, ensuring robust handling of topics, producers/consumers, durability, and retry mechanisms Drive API-first and MCP-native design for GTM integrations, leveraging RESTful APIs al

The MongoDB Query Execution Team is hiring software engineers who want to join us in developing a high performing, reliable and modular distributed query system. Our engineers work on implementing and maintaining execution algorithms, building new query language features, tuning database performance, and more to power our customers' critical workloads. This role can be based out of our Dublin office or remotely in Ireland. Relocation can be supported. Position Expectations Understand and improve current functionality of the MongoDB query engine Contribute high quality C++ code and give and solicit feedback in code reviews Identify, design, implement, test, and support new features related to query performance and robustness, query language enhancements, diagnostics for query performance problems, and integration with other products and tools Work constructively with peers to deliver excellent technical solutions Candidate Profile 5+ years of experience in systems programming Experience in databases and/or data management systems is a huge plus, but not a requirement Hands-on experience building industrial-strength software Solid computer science fundamentals, with strong competencies in data structures, algorithms, and software design/architecture Experience with large code bases, preferably in C++, C, Rust or a similar compiled language B.Sc in Computer Science or similar field, or equivalent practical experience Interest in the theory and practice of database query engines. Hands-on experience or M.Sc./Ph.D in the domain is a plus Success Measures In three months you’ll have contributed to the development of a project slated for the next major version, as well as fixed a few bugs in a minor version of our latest stable release series In six months, you’ll have taken on code review responsibilities and are independently delivering complex functionality and squashing bugs independently In twelve months, you’re leading the development of a new major feature and are h

We're looking for a Senior Engineer with a strong background in computer science fundamentals, systems design, experience in the Java ecosystem, streaming systems, and data-intensive applications to join our engineering team. In this role, you will be instrumental in designing, building, and optimizing the underlying data structures, algorithms, and database interactions that power our generative AI platform, code generation and migration tools. This involves crafting sophisticated orchestration layers, robust integration points, and high-performance data systems that seamlessly connect and leverage advanced AI capabilities for code generation and building a sophisticated data migration suite using a modern technology stack, which includes Java, Spring Boot, Kafka, Debezium, and React.You will work on critical components that ensure the scalability, efficiency, and reliability of our services, collaborating closely with AI researchers, product management and other engineers to design and implement cutting-edge products that solve complex customer challenges.. We are looking to speak to candidates who are based in Sydney for our hybrid working model. The ideal candidate for this role will have 6+ years of engineering experience in backend systems, distributed systems, or core platform development. Proficiency in one or several of Java, Rust, C/C++, and/or Python, with a strong understanding of systems-level programming, memory management, and performance tuning. Extensive experience with streaming data platforms such as Apache Kafka and Change Data Capture (CDC) tools like Debezium Extensive experience with relational data modeling and hands-on experience with at least one SQL database (Postgres, MySQL, etc) Exposure to client-side technologies such as JavaScript and React is a plus Good understanding of algorithms, data structures and their time and space complexity Curiosity, a positive attitude, and a drive to continue learning Excellent verbal and wri

We’re looking for a Software Engineer 3 to help bring Voyage’s embedding models - used for semantic search, retrieval, and AI-native experiences; to the platforms and environments where customers already run their workloads, beyond first-party MongoDB Atlas. You’ll join the broader Search and AI Platform organization and collaborate closely with the engineers building Voyage’s first-party inference. Together, we’re extending that platform across cloud marketplaces, third-party inference providers, and self-managed deployments so customers get the same Voyage models, behaving consistently, wherever they choose to run them. As a Software Engineer 3, you'll focus on building the systems, tooling, and deployment workflows that power third-party model delivery. You'll own key components of how Voyage models are packaged, validated, and deployed, work across teams to ensure tight integration with the core inference platform, and contribute to delivery surfaces designed for reliability, observability, and ease of use. We are looking to speak to candidates who are based in Sydney for our hybrid working model. What you'll do Port and tune the model server that runs Voyage embedding and reranking models: improving inference performance, consistency, and runtime behavior across environments Productionize new Voyage models for delivery beyond first-party Atlas, owning the packaging, configuration, and deployment workflows that get them running on AWS, Azure, GCP and more Design correctness, correlation, and performance validation that proves third-party deployments match first-party behavior Build operability into every surface: structured logging, metrics, diagnostics, and health checks with tools like Prometheus and OpenTelemetry Debug problems that span model servers, containers, deployment configuration, and partner cloud environments Work alongside Voyage's model-serving teams, and partner with GTM, SAs, TSEs, and strategic customers on the hardest external deployments Who

About the Role The worldwide data management software market is massive – IDC forecasts it to be $137.6 billion by 2026! At MongoDB, we are transforming industries and empowering developers to build amazing apps that people use every day. We are the leading modern data platform and were the first database provider to IPO in over 20 years. Join our team and be at the forefront of innovation and creativity. The Storage Layer Services Team is currently re-architecting the MongoDB Cloud Storage Layer. This is a relatively new team in MongoDB that sits at the heart of the next generation MongoDB Cloud Storage Architecture, and the team is working to build performant multi-tenant distributed storage services both to enhance our existing MongoDB cloud storage architecture and to power more of our customers' use cases more efficiently. We are looking for talented Senior Engineers to join the team and be founding members of the team, where you will play a crucial role in our multi-year roadmap. Our team champions a strong culture of inclusivity, diversity, and collaboration. If you want to work on a collaborative team that applies distributed systems fundamentals to deliver core storage features of a popular database, join us! Let’s change what’s possible for application developers, system architects, and database operators. We are looking to speak to candidates who are based in Sydney for our hybrid working model. Candidate Profile Minimum of 5 years of experience in programming, debugging, and performance tuning of distributed and/or highly concurrent software systems Strong systems fundamentals, including multi-threaded programming and performance profiling Experience with distributed systems Proven experience in building, deploying, and operating multi-tenant cloud services with a focus on operational excellence Familiarity with database internals or experience building core components for data processing systems Hands-on experience in developing performance-sensitive so

MongoDB’s Developer Productivity organization exists to help engineers build and deliver high-quality software through a highly effective software development process and a strong foundation of shared tools and services. We are looking for a Senior Director to lead our Pipeline team. This role is tasked with bringing together the major systems and experiences that power software delivery at MongoDB. The team’s mission is to provide a reliable, scalable, secure, and effective platform for ensuring fast software deployability, leveraging AI native approaches. We are open to in-office, flexible or remote hiring across Canada. The Team The Pipeline organization sits within Developer Productivity and is responsible for the systems, services, and user experiences that define MongoDB’s software delivery ecosystem. This is mission-critical infrastructure operating at substantial scale and supports a variety of software product delivery needs. Success in this role requires excellent product judgment for developer-facing experiences, strong systems and platform leadership, and the ability to align multiple teams around a cohesive strategy. Candidate Profile We’re looking for a senior engineering leader who can unify product-minded developer tooling with deep platform and operational excellence. The right candidate is passionate about developer productivity and has a track record of leading managers and teams through organizational growth, technical complexity, and cross-functional change. They should be comfortable owning a broad portfolio that spans developer experience, reliability and scale, release systems, telemetry, and operational health. They should also be able to work effectively with senior leaders and partners across engineering and product to set direction, allocate resources, and make trade-offs that balance near-term delivery with long-term platform function. The right candidate for this role will 12+ years of hands-on software engineering experience bui

MongoDB’s Developer Productivity organization exists to help engineers build and deliver high-quality software through a highly effective software development process and a strong foundation of shared tools and services. We are looking for a Senior Director to lead our Pipeline team. This role is tasked with bringing together the major systems and experiences that power software delivery at MongoDB. The team’s mission is to provide a reliable, scalable, secure, and effective platform for ensuring fast software deployability, leveraging AI native approaches. We are open to in-office, flexible or remote hiring across the US. The Team The Pipeline organization sits within Developer Productivity and is responsible for the systems, services, and user experiences that define MongoDB’s software delivery ecosystem. This is mission-critical infrastructure operating at substantial scale and supports a variety of software product delivery needs. Success in this role requires excellent product judgment for developer-facing experiences, strong systems and platform leadership, and the ability to align multiple teams around a cohesive strategy. Candidate Profile We’re looking for a senior engineering leader who can unify product-minded developer tooling with deep platform and operational excellence. The right candidate is passionate about developer productivity and has a track record of leading managers and teams through organizational growth, technical complexity, and cross-functional change. They should be comfortable owning a broad portfolio that spans developer experience, reliability and scale, release systems, telemetry, and operational health. They should also be able to work effectively with senior leaders and partners across engineering and product to set direction, allocate resources, and make trade-offs that balance near-term delivery with long-term platform function. The right candidate for this role will 12+ years of hands-on software engineering experience bui