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Track Engineer Jobs

3,811 active opportunities · Updated for October 2026

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Explore current track engineer jobs. Use filters to narrow by work mode, employment type, experience and date posted.

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Sentry
📍 Vienna• Full-time• Remote• €81K – €220K/yr
29 days ago

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role Agents are becoming the default way developers ship LLM-powered software, and they are miserable to debug. A single run fans out across model calls, tool calls, retries, handoffs between agents, and multi-turn conversations that only make sense as a whole. When one goes wrong, the developer usually has a log line and a shrug. Sentry's Agent Tracing turns that into something you can actually inspect: agent runs, tool calls, model interactions, token usage and cost, conversations you can replay message by message. As a Senior Software Engineer on the Telemetry Experience team, you'll own that product surface - Python/Django and Postgres on the backend, React and TypeScript on the frontend, sitting on top of Sentry's trace storage. You'll work with the SDK engineers who instrument the agent frameworks upstream and own everything customers touch downstream: the dashboards, the conversation views, the APIs, and the workflows that turn a confusing agent run into an obvious fix. In this role you will Own projects end to end. Take a problem from a rough customer complaint through scoping, design, implementation across the stack, rollout, and measurement. You'll write the design doc, cut the work into shippable pieces, and stay with it until the numbers move Build the views developers debug agents in. Multi-agent workflows, conversation replay, cost and token breakdowns, the moment where a run failed and why. Making a deeply nested, wildly variable trace legible is a genuinely hard interface problem Make the data underneath fast and queryable. Filtering and sorting millions of conversations, getting cost calculation ri

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Anthropic
📍 Ca New York City• $405K – $485K/yr
1mo ago

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 Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We believe powerful AI can compress a century of scientific progress into a decade. Claude Science is a big part of building toward that future. Claude Science is an AI workbench that gives researchers a single environment for work that today spans dozens of disconnected tools — literature, specialized databases, scientific computing, analysis, and publication-ready outputs. Claude Science already renders protein structures, genome tracks, and chemical structures natively, and coordinates multi-agent workflows with built-in review for citation and calculation errors — and we’re just getting started. Much of this is being built 0→1 right now: you’ll shape both the product and the architecture in a category no one has defined yet. You'll be a technical leader who thinks holistically about the end-to-end researcher experience, partners directly with our internal research team to push model capabilities into production, and carries real ownership over what we ship next. Our north star is accelerating scientific progress — across biology, chemistry, physics, and beyond — from early discovery through real-world application, by an order of magnitude. This work supports programs like Anthropic’s AI for Science Program and our rare disease research grants . What you'll do Ship fast against a roadmap you help shape: this is a product in a category no one has defined yet, and the highest-leverage problems are still unclaimed Interface directly with working scientists — academic labs, industry R&D teams, and research institutes — during key conv

ailogistics
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The opportunity We're looking for a Product Cybersecurity Engineer to help ensure that Polestar's products meet global cybersecurity standards and regulatory requirements throughout the vehicle lifecycle. In this role, you will work across concept, development, production, and post-launch operations, contributing to the implementation and validation of cybersecurity requirements that help safeguard our vehicle systems. Let us describe the challenge we offer As a Product Cybersecurity Engineer, you will play a key role in defining, integrating, and verifying technical security controls across our products. Working closely with R&D, suppliers, and cross-functional teams, you will support secure product development through threat analysis, secure design, cybersecurity validation, and regulatory compliance activities. This role is located at our HQ in Gothenburg, Sweden. What you'll do You will be responsible for implementing and validating cybersecurity requirements across the vehicle lifecycle while supporting compliance with standards and regulations such as ISO/SAE 21434 and UNECE R155. This includes: Define, decompose, trace, and maintain product cybersecurity requirements and assurance cases. Perform and/or support Threat Analysis and Risk Assessments (TARA) and risk treatment activities. Plan and execute cybersecurity validation and verification activities, including testing and reviews. Review supplier cybersecurity work products and support the closure of identified findings. Support the generation of technical evidence required for regulatory audits and type approvals. Collaborate with system architects, software and hardware teams, and functional safety teams to ensure secure integration. Contribute to the continuous improvement of security engineering methods, tools, and templates. Who you are You are an experienced cybersecurity engineer with a strong background in product or embedded cybersecurity. You enjoy working collaboratively across disciplines and a

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HackerRank Careers
📍 Hybrid In Bangalore• Hybrid
1mo ago

HackerRank helps companies like NVIDIA, Amazon, and Microsoft hire and upskill the next generation of developers based on skills, not pedigree. Our platform is trusted by over 2,500 of the world’s most innovative companies to build strong engineering teams ready for what’s next. Software has entered an era where humans and AI build side by side. As this shift accelerates, the definition of strong technical talent is changing. We give companies better ways to identify and invest in next-generation skills. People at HackerRank care deeply about the impact of their work and sweat the small details so our customers can be wildly successful with products they genuinely love to use. We move with urgency and believe great outcomes come from high standards. About the role Customer Experience Engineering is where customers, product, and engineering meet. As a CXE 1, you’ll investigate real technical problems across our platform, APIs, integrations, data, and customer workflows. You’ll learn to trace issues to root cause, communicate clearly with customers and internal teams, and build the judgment to own increasingly complex work independently. This is not a traditional support role built around scripts and handoffs. You’ll work in one shared CXE queue, use AI as part of your everyday engineering toolkit, and contribute to the knowledge, automation, and product improvements that prevent repeat problems. CXE 1 is designed as a transition into CXE 2 as your depth, independence, and customer readiness become consistently visible. What you will do Own standard and moderately complex customer issues from first investigation through resolution and closure. Debug web application, API, integration, authentication, configuration, and data issues using logs, developer tools, SQL, and established investigation patterns. Communicate clearly and empathetically across tickets, calls, incidents, and internal channels; ask precise questions, set expectations, and close every loop. Work with

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About Graphcore Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary Join our dynamic Software Infrastructure team and take a pivotal role in scaling and managing our infrastructure. You will develop essential tools and services that empower our broader software team. Your contributions will enhance the build, test, deployment, and productisation processes of our Machine Learning Software components. Work with our High-Performance Computing (HPC) AI platforms and gain invaluable experience in distributed systems. The Team An exciting opportunity to join a new team within the Software Operations group. The Build Engineering team is a new function within Software Infrastructure, which focuses on the overall process of building and integration of the Machine Learn ing S oftware S tack. You will work closely with the QA and development teams to get an understanding of how our ML SW stack is built, helping to ensure good build practices, and proving that the stack works together and is reproducible in secure, sandboxed environments. Responsibilities and Duties Developing our internal t

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About Graphcore Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary Join our dynamic Software Infrastructure team and take a pivotal role in scaling and managing our infrastructure. You will develop essential tools and services that empower our broader software team. Your contributions will enhance the build, test, deployment, and productisation processes of our Machine Learning Software components. Work with our High-Performance Computing (HPC) AI platforms and gain invaluable experience in distributed systems. The Team An exciting opportunity to join a new team within the Software Operations group. The Build Engineering team is a new function within Software Infrastructure, which focuses on the overall process of building and integration of the Machine Learn ing S oftware S tack. You will work closely with the QA and development teams to get an understanding of how our ML SW stack is built, helping to ensure good build practices, and proving that the stack works together and is reproducible in secure, sandboxed environments. Responsibilities and Duties Developing our internal t

pythondockerlinux
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About Graphcore Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary Join our dynamic Software Infrastructure team and take a pivotal role in scaling and managing our infrastructure. You will develop essential tools and services that empower our broader software team. Your contributions will enhance the build, test, deployment, and productisation processes of our Machine Learning Software components. Work with our High-Performance Computing (HPC) AI platforms and gain invaluable experience in distributed systems. The Team An exciting opportunity to join a new team within the Software Operations group. The Build Engineering team is a new function within Software Infrastructure, which focuses on the overall process of building and integration of the Machine Learn ing S oftware S tack. You will work closely with the QA and development teams to get an understanding of how our ML SW stack is built, helping to ensure good build practices, and proving that the stack works together and is reproducible in secure, sandboxed environments. Responsibilities and Duties Developing our internal t

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Figma
📍 Ca New York• Full-time• From $258K/yr
2mo ago

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! Figma’s Observability engineering team builds and operates the systems that give us deep visibility into the health, performance, and efficiency of our platform. From metrics, logs, and traces to cost attribution and budgeting, this team ensures that engineers across Figma can detect issues quickly, understand system behavior at scale, and make informed decisions about reliability and spend. The team owns and evolves our core observability stack—including platforms like Datadog, shared instrumentation libraries, and the agents and operators that power telemetry collection—while continuously raising the bar on signal quality and operational clarity. This team ensures that engineers across Figma can detect issues quickly, understand system behavior at scale, and make informed decisions about reliability. The team owns and evolves our core observability stack—including platforms like Datadog, shared instrumentation libraries, the agents and operators that power telemetry collection, and a host of internally developed components to power AI Trace Observability —while continuously raising the bar on signal quality and operational clarity. As the Engineering Manager for Observability, you will lead a team of five engineers responsible for shaping the future of visibility and efficiency at Figma. You’ll define the strategy for instrumentation standards and cost transparency, drive initiatives to optimize observability footprint and spend, and explore innovative AI-driven approaches to anomaly detection

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MDM TechnologyMDM Technology, a company affiliated with Dun & Bradstreet, provides enterprise-grade master data management (MDM) solutions that help organizations create a single, trusted view of business entities. By cleansing, matching, linking, and enriching data, anchored by the global standard D‑U‑N‑S® Number business identifier, MDM Technology enables accurate identity resolution across systems to support analytics, compliance, and AI workflows across industries. The Senior Quality Assurance Engineer ensures our software meets user and product needs. The role creates and maintains project test plans, defines and tracks quality assurance metrics, collects and analyzes data for software process evaluation and improvements, and integrates them into business processes combining deep technical expertise in API and Integrations testing and Automation. This role must show a passion for AI enabled Software Quality practices Leveraging modern AI tools to improve testing efficiency, accelerate release cycles, and enhance software reliability across complex enterprise integration.

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OpenAI
📍 San Francisco• Full-time
2mo ago

About the team The Agent Enablement AI Deployment Engineering (ADE) team works across engineering, product, design, partnerships, and strategic customers to grow an open ecosystem of agent-enabled sites and services. We help partners adopt the OpenAI tech stack related to identity, permissioning, agent-auth primitives so users can safely connect ChatGPT and Codex to the tools, services, and workflows they already use. Our team also works with external partners on defining the standards for agent access, marketplace offerings as well as other agent enablement initiatives to ensure users of ChatGPT and Codex go from intent to task completion seamlessly. About the role We are looking for an AI Deployment Engineer to help strategic partners design, build, validate, launch, and operate agent enablement integrations across web applications, connectors, APIs, CLIs, MCP servers, and developer tools. This is a hands-on, partner-facing product engineering role for someone who can contribute to the platform itself, lead sophisticated technical engagements, and turn ambiguous identity and agent-workflow requirements into secure, production-ready integrations. You will work across partner product and engineering teams and OpenAI’s product, engineering, design, partnerships, legal, policy, security, support, and go-to-market teams. You will identify high-value user journeys, choose the right integration path, prototype and review architectures, write code, run evaluations and dogfood, trace failures end to end, guide launch and rollout, and support post-launch iteration. The best person for this role moves fluidly between full-stack code, OAuth/OIDC and identity systems, product judgment, project leadership, and clear communication with engineers and executives. This role is a fit for a product-minded engineer who wants to stay close to users and partners while going deep on authentication, permissions, reliability, safety, and developer experience. The principle objective is to

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2mo ago

Join the MongoDB Server Query Optimization team, and help us build a world-class distributed open-source query optimizer. Our team plays a crucial role in the experience and performance of data processing. We are responsible for the MongoDB Query Language and the lifecycle of each query, through parsing, optimization and plan selection. We have tons of interesting problems to solve with a direct impact on users for transactional, time-series, and analytical workloads. The team is endeavoring to systematically rewrite every major component of our optimization and execution systems. We need your help to design and build the heart of a distributed, flexible schema, document database. This role can be based remotely in the U.S. or Canada, limited to Eastern or Central time zones only. Candidate Profile 5+ years of experience in data management systems, distributed systems, or large-scale backend engineering Experience with building production-level code with a large user base, robust design structure and rigorous code quality Degree in Computer Science or similar field, or equivalent practical experience, with strong competencies in data structures, algorithms, and software design/architecture Experience with large code bases written in C++ or another systems programming language. You'll need to trace down defects, estimate work complexity, and design evolution and integration strategies as we rewrite different components of the system A strong foundation in core database internals is essential. While direct experience in query optimization is a massive bonus, it is not a prerequisite. We are also excited to meet candidates with strong backgrounds in compilers, language transpilers, or distributed storage systems Position Expectations Innovate in the area of flexible schema databases. Help us build a world-class query optimization system Research state-of-the art query systems to inform our design Leverage deep knowledge of the strength and weakness of the product and o

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About Us OpenFX is on a mission to move money as freely as data, unrestricted by time zones, banking hours, or legacy systems. We are building the infrastructure that will power the next generation of cross-border payment systems for institutions. The team's execution has been exceptional, and we're scaling at a remarkable pace. Our stellar early team comes with experience in companies like J.P. Morgan, Goldman Sachs, FalconX, Paypal, Affirm, Polygon, Kraken, Nium & others. We're backed by Accel, Lightspeed, NfX and other top-tier investors. Role Overview We're hiring a frontend-heavy Full Stack Engineer for our Trading team — the team that owns the client's entire trade experience. Trading owns quote generation, pricing strategy, the spread engine, and the trade lifecycle across GUI, API, and soon conversational AI. Our north star is Total Payment Volume, with Gross Revenue as the control metric. You will own the client-facing surface of that experience. This is where an institutional client sees a live quote, understands the price and fees, commits to a trade, and tracks it through to settlement. You will own architecture for these flows — state management, data fetching, error handling, and performance — and be trusted with the correctness of what the client sees. You will also work across the stack. You'll build and extend the APIs your surfaces depend on, model the data behind them, and ship the backend piece of a feature rather than waiting on someone else to unblock you. You don't need deep backend systems experience for this role, but you do need to be genuinely comfortable there. We're specifically looking for someone with a trading background. Think a crypto exchange, brokerage, or trading platform (CoinDCX, Groww, CoinSwitch Kuber, or similar). Key Responsibilities Own the architecture of critical client trade flows — quote and pricing surfaces, trade initiation, and status and settlement tracking — across GUI, API and conversational AI. Design fronte

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2mo ago

About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The Payments organization owns some of Stripe’s most critical payment flows and a platform that processes hundreds of billions of dollars in payments a year. Our team builds and scales the infrastructure and financial partner integrations that enables Stripe to accept, manage, and payout money across many countries, currencies, and payment methods. Our work is core to Stripe’s business, and thousands of developers use our platform and infrastructure to create valuable products and services that billions of people use. Our goal is to increase the GDP of the internet by making it easy to build global products, services, and platforms that handle money. Technical Operations roles in Payments are a dynamic and key component of Stripe's success. Focused on financial partner integrations and funds flow expansion, we sit at the intersection of product/platform engineers and financial partners, connecting them to ensure that everyone thrives and nothing is lost in translation. Our team partners closely with various finance and infrastructure engineering teams to ensure timely delivery of accurate data between financial partners, internal stakeholders, and Stripe leaders. We report and trace all of Stripe’s money movement transactions, including payments in more than 30 currencies and dozens of countries. You’ll own building and scaling Stripe’s manual and programmatic financial reporting and reconciliation processes for intra-company and outgoing money m

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OpenAI
📍 San Francisco• Full-time• $197K – $280K/yr
2mo ago

About the team The Applied AI Engineering, Sign in with ChatGPT team works across engineering, product, design, partnerships, and strategic customers to grow an open ecosystem of agent-enabled sites and services. We help partners adopt the OpenAI tech stack related to identity, permissioning, agent-auth primitives so users can safely connect ChatGPT and Codex to the tools, services, and workflows they already use. Our team also works with external partners on defining the standards for agent access, marketplace offerings as well as other agent enablement initiatives to ensure users of ChatGPT and Codex go from intent to task completion seamlessly. About the role We are looking for an Applied AI Engineer to help strategic partners design, build, validate, launch, and operate agent enablement integrations across web applications, connectors, APIs, CLIs, MCP servers, and developer tools. This is a hands-on, partner-facing product engineering role for someone who can contribute to the platform itself, lead sophisticated technical engagements, and turn ambiguous identity and agent-workflow requirements into secure, production-ready integrations. You will work across partner product and engineering teams and OpenAI’s product, engineering, design, partnerships, legal, policy, security, support, and go-to-market teams. You will identify high-value user journeys, choose the right integration path, prototype and review architectures, write code, run evaluations and dogfood, trace failures end to end, guide launch and rollout, and support post-launch iteration. The best person for this role moves fluidly between full-stack code, OAuth/OIDC and identity systems, product judgment, project leadership, and clear communication with engineers and executives. This role is a fit for a product-minded engineer who wants to stay close to users and partners while going deep on authentication, permissions, reliability, safety, and developer experience. The principle objective is to help pa

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Micron
📍 Longmont Max Office• Full-time
2mo ago

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Micron's Data Center Workload Engineering team tests how memory and storage products perform in complete data center systems. We deploy customer-representative AI, database, virtualization, and software-defined storage workloads in production-class labs. We trace I/O from the application through the system to the SSD to explain performance and identify opportunities to improve it. As a Principal Systems Performance Engineer, you will lead complex performance studies from the initial question through the final recommendation. You will personally lead the hardest investigations while setting technical direction for the team. Your work will guide SSD architecture and product development and help customers get the best performance from Micron products. This is a hands-on senior individual-contributor role. Key Responsibilities Lead application performance studies on enterprise servers, GPU-accelerated systems, and data center storage platforms. Deploy customer-representative workloads across one or more areas, such as AI training and inference, checkpointing, KV-cache offload, data preparation, databases, virtualization, and software-defined and object storage. Develop test plans with clear hypotheses, realistic configurations, appropriate controls, and repeatable methods. Instrument systems and trace I/O from the application through the software and storage stack to the SSD. Measure application throughput

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