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Backend Compiler Engineer Jobs

1,931 active opportunities · Updated for October 2026

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C
Coinbase
📍 - USA• Full-time• Remote• From $186.1K/yr
1mo ago

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . Senior Software Engineer, Simple Trade Experience We're hiring a Senior Software Engineer to join the Simple Trade Experience team within the Consumer & Business group. This team powers the critical buy, sell, and convert journeys on the Simple interface of the Coinbase app and website, supporting multiple trading types and assets for millions of users worldwide. You'll own highly performant, available, and consistent backend and frontend systems that directly enable customers to trade with confidence at web-scale. What you'll do: Own the design and delivery of highly performant, available, and consistent systems powering trading for millions of users worldwide Architect robust, extensible systems that support multiple trading types and assets (Spot, Limit, Recurring, and more) while maintaining reliability at web-scale Partner closely with product and design to define and ship a best-in-class trading experience across web and mobile Drive production service evolution, scaling and maintaining critical trading infrastructure as traffic and product scope grow Strengthen engineering quality across the team through rigorous code reviews, mentorship, and knowledge sharing Required Skills and Experience: 5+ years of experience in software engineering with demonstrated success building and scaling production services handling web-scale traffic Proven track record design

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Baseten
📍 San Francisco• Full-time
1mo ago

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Are you passionate about advancing the application of artificial intelligence? We are looking for a Software Engineer focused on ML performance to join our dynamic team. This role is ideal for someone who thrives in a fast-paced startup environment and is eager to make significant contributions to the exciting field of LLM Inference. If you are a backend engineer who thrives on making things faster and is excited about open-source ML models, we look forward to your application. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Model Performance team: Baseten Embeddings Inference: The fastest embeddings solution available The Baseten Inference Stack Driving model performance optimization RESPONSIBILITIES Implement, refine, and productionize cutting-edge techniques (quantization, speculative decoding, kv cache reuse, chunked prefill and LoRA) for ML model inference and infrastructure. Deep dive into underlying codebases of TensorRT, PyTorch, TensorRT-LLM, vllm, sglang, CUDA, and other libraries to debug ML performance issues. Apply and scale optimization techniques across a wide range of ML models, particularly large language models. Collaborate with a diverse team to design and implement innovative solutions. Own projects from idea to production. REQUIREMENTS Bachelor's, Master's, or Ph.D. degree in Computer Science, Engineering, Mathematics, or related field. Experience with one

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Baseten
📍 San Francisco• Full-time
1mo ago

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE As a Software Engineer on the Internal Tooling team, you will own the internal operating system that sits at the heart of how Baseten operates. Capacity helps unlock revenue by carefully balancing supply and demand. The operating system manages all aspects of the customer lifecycle: from onboarding to managing complex customer SLA requirements. This role is for engineers who want to own a product end to end, not just implement tickets. You will work directly with the Capacity, Sales, and Engineering teams to understand requirements, define solutions, and ship software that removes friction from some of the most high-stakes workflows in the company. If something is slow, manual, or error-prone in the capacity fulfillment lifecycle, you will be the one to fix it. You are a strong fit if you have strong product intuition, move fast without sacrificing quality, and take satisfaction in building tools that make the people around you measurably more effective. RESPONSIBILITIES Own the Capacity product end to end: scoping, design, implementation, and iteration based on feedback from internal stakeholders Translate complex operational requirements from Capacity, Sales, and SRE teams into clean, ergonomic product experiences Build and maintain full-stack features across the Capacity toolchain, including UI surfaces, APIs, and backend services Identify workflow bottlenecks and manual processes across the capacity lifecy

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B
Baseten
📍 San Francisco• Full-time
1mo ago

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE We’re looking for a seasoned Frontend Engineer to craft performant and delightful user experiences across Baseten’s core platform. You’ll own critical parts of our web application stack and collaborate cross-functionally with product, design, and backend teams to launch impactful features that help users deploy and manage AI systems at scale. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Core Product team: Rolling Deployments Model APIs for frontier models Model training built for production inference RESPONSIBILITIES Design, implement, and maintain responsive, accessible, and user-friendly frontend interfaces using React and TypeScript Collaborate closely with product designers to turn complex ideas into elegant, intuitive UIs Optimize application performance and reliability, with a focus on rendering speed and responsiveness Drive major frontend initiatives, including partnering with backend teams to define APIs and test and refine end-to-end flows Establish best practices, and mentor other engineers on frontend technologies Build reusable component libraries and frontend infrastructure that accelerate product development Partner with backend and platform teams to define and refine APIs and end-to-end flows REQUIREMENTS 5+ years of experience building production-grade web applications Deep expertise in React, TypeScript, and modern web development tooling Track record of bu

typescriptreactmachine learning
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S
1mo ago

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. We’re looking for a Principal Engineer to join the ML Platform team at Synthesia. Our team builds and operates the systems that allow researchers and product teams to train, serve, and deploy generative models reliably and efficiently . This includes research infrastructure, production serving systems, internal tooling, and the platform interfaces that connect them. A growing part of our mission is making these systems more automation-friendly and agent-oriented , so that workflows can increasingly be operated through reliable tooling rather than manual effort. We’re looking for a strong generalist with a systems mindset: someone who is comfortable working across infrastructure, backend systems, and tooling, and who has seen ML systems in practice. this is not a pure ML Engineer role. We’re especially interested in people who think deeply about reliability, scalability, performance, and resource efficiency in complex production environments. This is a hands-on IC role with significant ownership. You’ll help shape how our ML platform evolves as we scale the number of models, workloads, tools and teams relying on it. What you’ll do Design and improve the platform systems that support model training, evaluation, an

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A
Anyscale
📍 Remote• Full-time
1mo ago

About Anyscale: At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the role Ray aims to provide a universal API for building distributed applications. To achieve this goal requires a distributed system with high levels of performance and reliability. We're looking for engineers with systems software experience that are interested in contributing to the Ray backend. About the Ray Core Team The Ray Core team develops and maintains the Ray C++ backend (e.g., distributed scheduler, language runtime integration, I/O and memory subsystems). We are responsible for the reliability, scalability, and performance of Ray as well as ensuring that Ray provides the right feature set to support higher level libraries and use cases. The team works on a balance of new features / distributed libraries, test infra improvements, debugging, and longer-term architectural improvements to Ray. A snapshot of projects you can work on: Optimizing performance of large-scale workloads on Ray Stability and stress testing infrastructure Improving fault tolerance (HA) As part of this role, you will: Leading cross-team projects while mentoring junior team members Develop high quality open source software to simplify distributed programming (Ray) Identify, implement, and evaluate architectural improvements

restmachine learningai
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A
Anyscale
📍 Remote• Full-time
1mo ago

About Anyscale: At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the role: Ray aims to provide a universal API for building distributed applications (e.g. a machine learning pipeline of feature engineering, model training, and evaluation). Data is usually a core element connecting these different stages, and therefore plays a critical role in Ray’s usability, performance, and stability. We are looking for strong engineers to build, optimize, and scale Ray’s Datasets library and data processing capabilities in general. About the Ray Data team: The Ray Data team currently develops and maintains the Ray Datasets library, which is already powering critical production use cases (e.g. large scale data compaction at Amazon , and ML pipeline at Alibaba ). Ray Datasets is a Python library built on top of Apache Arrow and Ray Core (Ray’s C++ backend), and the Ray Data team interacts closely with Ray Core components including the scheduler and the memory & I/O subsystems. The Ray Data team also works closely with Ray’s ML libraries including Train, RLlib, and Serve. A snapshot of projects you will work on: - Performance of Ray Datasets at large scale (leveraging Arrow primitives, optimizing Ray object manager, etc.) - Integration with ML training and data sources - Stability an

pythonmachine learningai
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A
Anyscale
📍 Remote• Full-time
1mo ago

About Anyscale: At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the role Ray aims to provide a universal API for building distributed applications. To achieve this goal requires a distributed system with high levels of performance and reliability. We're looking for engineers with systems software experience that are interested in contributing to the Ray backend. About the Ray Core Team The Ray Core team develops and maintains the Ray C++ backend (e.g., distributed scheduler, language runtime integration, I/O and memory subsystems). We are responsible for the reliability, scalability, and performance of Ray as well as ensuring that Ray provides the right feature set to support higher level libraries and use cases. The team works on a balance of new features / distributed libraries, test infra improvements, debugging, and longer-term architectural improvements to Ray. A snapshot of projects you can work on: - Optimizing performance of large-scale workloads on Ray - Stability and stress testing infrastructure - Improving fault tolerance (HA) As part of this role, you will: Develop high quality open source software to simplify distributed programming (Ray) Identify, implement, and evaluate architectural improvements to Ray core Improve the testing process for Ray to make re

restmachine learningai
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S
Synthesia
📍 London• Full-time
1mo ago

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. We’re looking for an Engineer to join the ML Platform team at Synthesia. Our team builds and operates the systems that allow researchers and product teams to train, serve, and deploy generative models reliably and efficiently . This includes research infrastructure, production serving systems, internal tooling, and the platform interfaces that connect them. A growing part of our mission is making these systems more automation-friendly and agent-oriented , so that workflows can increasingly be operated through reliable tooling rather than manual effort. We’re looking for a strong generalist with a systems mindset: someone who is comfortable working across infrastructure, backend systems, and tooling, and who has seen ML systems in practice. this is not a pure ML Engineer role. We’re especially interested in people who think deeply about reliability, scalability, performance, and resource efficiency in complex production environments. This is a hands-on IC role with significant ownership. You’ll help shape how our ML platform evolves as we scale the number of models, workloads, tools and teams relying on it. What you’ll do Design and improve the platform systems that support model training, evaluation, and product

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C
Coder
📍 United Kingdom• Full-time
1mo ago

As an Engineering Manager on Coder’s Agentic Engineering team, you’ll lead engineers building and evolving the systems behind our agentic development experience. You’ll help make agents more capable, reliable, and useful across real development environments. You’ll guide technical direction, grow the team, and keep execution sharp. You’ll work closely with Engineering, Product, and Design across the agent harness, integrations, and developer workflows. What you’ll do here Lead and grow a team within our Agentic Engineering organization. Set technical direction across the agent harness, integrations, and workflows. Stay close to the code and contribute to architecture and implementation decisions. Evolve agent execution, tool use, context management, streaming, and long-running workflows. Extend our provider-agnostic architecture as models and capabilities change. Partner with Product and Design to turn agent capabilities into useful developer experiences. Improve reliability, performance, and operability across agentic systems. Coach engineers, raise the technical bar, and create clarity around priorities and tradeoffs. What we’re looking for Experience managing and growing software engineering teams. Strong hands-on engineering 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. Strong technical judgment and comfort working through ambiguity. A track record of helping engineers grow while maintaining a high execution bar. 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 enviro

typescriptreactaws
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Writer
📍 New York• Full-time
1mo ago

🚀 About WRITER WRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Seattle, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI. 📐 About the role We’re seeking a highly skilled fullstack software engineer to join our engineering team building advanced AI-driven agent systems that execute autonomous workflows, orchestrate multi-step tasks, and extend human capacity across enterprise applications. In this role, you’ll play a key part in designing, building, and scaling next-generation AI agents that integrate with enterprise data and services to solve real-world problems. You will collaborate with cross-functional teams to turn complex agent concepts into production-ready systems. 🦸🏻‍♀️ What you'll do Design, implement, and maintain scalable, secure agent-driven services and systems that autonomously accomplish tasks using modern AI frameworks. Develop and enhance robust infrastructure and high-throughput APIs, focusing on core agent capabilities such as memory, communication channels, skills, intelligent decision logic, security and workflow management. Integrate agent capabilities with backend services

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Senior Software Engineer - Analytics Compute Platform Team About the Role & Team Every chart, insight, and experiment result a customer sees in Amplitude passes through the compute layer that this team owns. Our team sits between Amplitude's front-end analytics products/ rest APIs/ MCPs and Nova, our proprietary analytics database, and owns the compute API that translates a user's question into a fast, correct answer. Our mandate: enable a highly performant, reliable, and flexible way to compute insights. Those three goals are often in tension the more flexible we make the system, the harder it is to keep it fast and simple, and a lot of the interesting engineering work on this team lives in that tradeoff. Day to day, you'll work closely with engineers on data management, marketing analytics, Session Replay, Experiment, CDP, Query, and various product teams, since they're all consumers of what we build. As a Senior Software Engineer, you will Design and build core parts of the query/compute engine that powers analysis across Amplitude's product suite Evolve the compute API and semantic layer that other engineering teams build features on top of, so that it can support a more generic table Help unify and evolve our core data model, including how non-event data (profile properties, lookup tables, etc.) is represented alongside event data Improve the performance, reliability, and scalability of query planning and execution on the Amplitude query engine Partner with teams across Session Replay, Experiment, CDP, Query, and frontend to understand their needs and shape the compute layer around them Take ownership of projects end-to-end, from design through rollout You'll be a great addition to the team if you have Strong backend or distributed-systems engineering experience, ideally touching OLAP databases, query engines, or data infrastructure Experience with SQL, query planning/execution, or building APIs that many other engineering teams depend on Comfort reasoning

sqlgitrest
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Writer
📍 London• Full-time
1mo ago

🚀 About WRITER WRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Seattle, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI. 📐 About the role We’re seeking a highly skilled fullstack software engineer to join our engineering team building advanced AI-driven agent systems that execute autonomous workflows, orchestrate multi-step tasks, and extend human capacity across enterprise applications. In this role, you’ll play a key part in designing, building, and scaling next-generation AI agents that integrate with enterprise data and services to solve real-world problems. You will collaborate with cross-functional teams to turn complex agent concepts into production-ready systems. 🦸🏻‍♀️ What you'll do Design, implement, and maintain scalable, secure agent-driven services and systems that autonomously accomplish tasks using modern AI frameworks. Develop and enhance robust infrastructure and high-throughput APIs, focusing on core agent capabilities such as memory, communication channels, skills, intelligent decision logic, security and workflow management. Integrate agent capabilities with backend services

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M
1mo ago

What we're building Mutiny is the self-improving AI infrastructure for GTM teams to execute faster and close more revenue. Our ambition is to do for revenue velocity what Cursor and Claude Code did for engineering velocity. With Mutiny, everyone in sales and marketing gets a bench of GTM athletes that handle any work across their revenue motion and learn from what's actually moved their deals. In April we re-launched the product as an agent-first platform. Anthropic showcased us as a leader in AI GTM. MRR is growing more than 70% month-over-month, with customers like Uber, Rippling, and Snowflake. We're backed by Sequoia, YC, and Insight, and we're building a generational company. The opportunity Most engineers spend their career making predictable systems faster. You'll spend yours making non-deterministic ones trustworthy. As a senior engineer on our AI product team, you'll architect the Campaign Builder and Agent experiences marketers and sellers open every day to go from idea to personalized assets in minutes. You'll partner directly with product, design, and the founders to define what an agent-first GTM platform should feel like, and your calls on architecture, evals, and guardrails compound across thousands of customer accounts. This role is in person in New York City, five days a week, and we ship weekly. What you'll own The core agent surfaces. Architect and ship the Campaign Builder and Agent experiences end-to-end. Frontend, backend, prompts, evals, the whole stack. Reliability on top of LLMs. Make non-deterministic models feel deterministic at the surface. Build the retries, fallbacks, and orchestration so the customer never sees the failure mode. Evals and guardrails. Define how we measure quality, catch regressions, and keep brand and tone consistent across thousands of customer accounts. Speed and feel. AI products live or die by latency and the loop between intent and output. You'll obsess over both, and use coding agents and agent networks to ship f

typescriptpythonai
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About The Role & Team We’re looking for a Fullstack Engineer to join the Core Analytics team, the group behind our flagship analytics product loved by thousands of product teams worldwide. You’ll work with our Product Manager and Designer to define, build, and ship end-to-end features that elevate the Analytics experience. You’ll own your impact from shaping product direction to delivering performant, reliable, and delightful user experiences. Our engineers are customer-focused and solve complex data problems to deliver a better user experience. We deliver value quickly and iteratively. If you’re passionate about building exceptional data-powered experiences that help businesses understand their customers, we’d love to meet you. The team’s mission is to deliver a fast, intuitive, and reliable Analytics platform that empowers customers to confidently uncover insights about their products while driving infrastructure initiatives that strengthen and scale the platform. As a Staff Engineer, you will: Work with Product Management and Design to generate and turn novel ideas for solving customer problems into engineering solutions Drive business impact through owning the end-to-end delivery of projects Have a strong critical thinking and problem-solving mindset with attention to detail Get involved in performance optimization and scaling efforts Drive business impact through leading the highest-leverage projects Have interest or experience in technical leadership of an engineering team Mentor and contribute to the success of other engineers on the team You'll be a great addition to the team if you: 7+ years of experience building and improving robust, scalable backends and developing interactive, user-facing applications or websites. Understand the whole stack and flow of user-facing web applications. Backend experience with application backends, microservices, and supporting high-throughput ingestion systems Strong critical thinking and problem-solving mindset with at

javascripttypescriptpython
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