Distributed Systems Engineer Jobs

Position Overview: We are looking for a Senior Software Engineer to drive technical excellence, architect complex systems, and elevate our engineering team. You will own critical technical decisions, lead major initiatives from conception to delivery, and set the standard for engineering quality across our products. As a senior engineer, you will architect and lead the development of sophisticated AI-enabled features and infrastructure. This includes designing MCP server architectures, building advanced RAG systems, implementing agentic AI workflows, and establishing patterns that scale across our product portfolio. You will combine deep technical expertise in both traditional software engineering and AI/ML to deliver production-grade solutions. What You'll Do Lead the design and implementation of AI integration infrastructure (MCP servers, orchestration layers, API gateways) Build sophisticated AI features including advanced RAG systems, agentic workflows, and multi-step reasoning Establish AI engineering best practices, security patterns, and quality standards Lead technical initiatives from requirements through production deployment Make critical architectural decisions balancing performance, scalability, cost, and maintainability Design AI evaluation frameworks and implement quality benchmarks Debug and resolve complex production issues across traditional and AI systems Required Qualifications Tech Stack Core: Node.js, React, TypeScript, AWS, PostgreSQL, MSSQL, Docker AI & Integration: Python, MCP, AWS Bedrock, LangGraph/Semantic Kernel, Vector Databases, RAG Core Technical Skills 5+ years professional development with proven track record of delivering complex systems Strong Node.js and JavaScript/TypeScript expertise Advanced React and frontend architecture skills Extensive AWS architecture experience Expert PostgreSQL database design, optimization, and performance tuning Deep understanding of microservices, distributed systems, and

Roles and Responsibilities Write maintainable/scalable/e?cient code. Work in a cross-functional team, collaborating with peers during the entire SDLC. Follow coding standards, unit-testing, code reviews etc. Follow release cycles and commitment to deadlines. Qualifications & Experience Experience level of 3 to 5 years of experience in very large scale applications. Fair understanding in problem solving skills, data structures and algorithms. Experience with distributed systems handling large amounts of data. Fair understanding in coding skills in Java/J2EE, Web technologies, RDBMS/messaging.

Roles and Responsibilities Write maintainable/scalable/code Work in a cross-functional team, collaborating with peers during the entire SDLC. Follow coding standards, unit-testing, code reviews etc. Follow release cycles and commitment to deadlines. Qualifications & Experience Experience level of 3 to 6 years of experience in very large scale applications. Fair understanding in problem solving skills, data structures and algorithms. Experience with distributed systems handling large amounts of data. Fair understanding in coding skills in Java/J2EE, Web technologies, RDBMS/messaging.

Roles and Responsibilities Write maintainable/scalable/e?cient code. Work in a cross-functional team, collaborating with peers during the entire SDLC. Follow coding standards, unit-testing, code reviews etc. Follow release cycles and commitment to deadlines. Qualifications & Experience Experience level of 3 to 5 years of experience in very large scale applications. Fair understanding in problem solving skills, data structures and algorithms. Experience with distributed systems handling large amounts of data. Fair understanding in coding skills in Java/J2EE, Web technologies, RDBMS/messaging.

Roles and Responsibilities- ? Write maintainable/scalable/efficient code. ? Work in a cross-functional team, collaborating with peers during the entire SDLC. ? Follow coding standards, unit testing etc. ? Follow release cycles and commitment to deadlines. Qualifications & Experience ? 1+ years of experience in large scale applications. ? Problem solving skills, data structures and algorithms. ? Experience with distributed systems handling huge data. ? Coding skills in Java/J2EE. ? Good understanding of Web Technologies. ? Good understanding of any RDBMS and/or messaging.

Senior Software Engineer - Observability and Reliability About the Role We are growing the engineering team and looking for engineers who have the chops to build and deliver world-class technology. You will be part of a talented team of engineers with a shared mission to make data easily accessible. What You Will Be Doing Build observability tools and platforms, including: metrics, logging, distributed tracing, dashboarding, alerting, application performance management Build with modern tools and languages like Go, Open Telemetry and Kubernetes Participate in on-call rotation and ensure uptime of services Create runtime tools/processes that optimize cloud triaging and limit downtime Define best practices around making our systems and services measurable Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies. We expect successful candidates to be coding a majority of their time Qualifications We Need Strong Computer Science fundamentals 5+ years industry experience building and maintaining high-quality software, especially software other engineers use You apply a product mindset to infrastructure systems and feel accomplished enabling others Desire to be a great teammate and have fun at work Strong sense of craftsmanship, and a healthy academic curiosity Qualifications We Want (also, skills you’ll learn!) Experience building systems for data analytics Distributed systems monitoring and profiling skills Knowledge of cloud application security models Administered cloud service infrastructure (GCP, AWS, Azure) Startup experience Additional Job details Additional Job details The base salary range for this position is $170k - $240k annually. Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize e

JOB TITLE Site Reliability Engineer A CAREER WITH POINT72’S TECHNOLOGY TEAM As Point72 reimagines the future of investing, our Technology group is constantly improving our company’s IT infrastructure, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts experimenting, discovering new ways to harness the power of open-source solutions, and embracing enterprise agile methodology. We encourage professional development to ensure you bring innovative ideas to our products while satisfying your own intellectual curiosity. WHAT YOU’LL DO You will play a highly critical operational role where you will apply a combination of software and systems engineering skills to develop and maintain a complex set of distributed, real-time systems that serve critical stakeholders in Point72’s Global Macro business. You will focus on optimizing the operations of existing systems and infrastructure in an efficient manner, through a strict adherence to automation and tooling Specifically, you will: Build out foundational technical components of an extensive SRE program across multiple complex systems, both new and existing • Collaborate with our development and quant teams to ensure that ongoing change is consistent with a pre-determined, measurable set of SLOs spanning multiple complex user interactions with our systems • Monitor system capacity and performance, identifying and addressing potential future bottlenecks and sources of instability before they become impactful to our stakeholders • Review and provide feedback on automation code developed by peers to maintain high standards of code quality and efficiency • Troubleshoot and resolve system issues, analyzing their impact on infrastructure and service operations • Participate in or lead design reviews with peers and stakeholders, evaluating and selecting the best technologies and automation strategies for our needs WHAT’S REQUIRED We are looking for highly motivated, proactive engineers

Here's a summary of the role: Do you love building scalable cloud platforms and solving complex engineering problems with modern technologies? As a Senior Software Engineer at Diligent, you'll design and deliver high-performing , serverless applications that power our global SaaS platform. You'll work extensively with TypeScript, Node.js, AWS, and event-driven microservices, owning services from design to deployment and production monitoring. This is an opportunity to influence technical decisions, mentor engineers, and explore how AI can transform software development and engineering productivity. If you're passionate about cloud-native architectures, distributed systems, and building software that scales to millions of users, we'd love to meet you. Here's a breakdown of what you'll do (not all of it, just the important stuff): Design and build scalable backend services and event-driven microservices using TypeScript and AWS. Develop secure APIs and integrations that power reporting, analytics, and dashboard experiences. Build and maintain serverless solutions using AWS services such as Lambda, EventBridge , SQS, and DynamoDB. Drive engineering excellence through testing, observability, automation, and production readiness practices. Contribute to infrastructure-as-code and CI/CD pipelines using AWS CDK and modern DevOps practices. Mentor engineers, participate in architecture discussions, and champion the use of AI tools to improve development efficiency. These are the essentials you'll need to get an interview: 6-8 years of professional software engineering experience. Strong experience with TypeScript, Node.js, and modern backend development patterns. Hands-on experience building cloud-native applications on AWS. Strong understanding of serverless architectures and event-driven microserv

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our product in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will be responsible for owning large new areas within our product, working across backend, frontend, and interacting with LLMs and ML models. You will solve hard engineering problems in scalability and reliability. You will: Own large new areas within our product Work across backend, frontend, and interacting with LLMs and ML models Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Be able, and willing, to multi-task and learn new technologies quickly Ideally you'd have: 7+ years of full-time engineering experience, post-graduation Experience scaling products at hyper growth startups Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies Proficient in Python or Javascript/Typescript, and SQL Experience with Kubernetes Experience with major cloud providers (AWS, Azure, GCP) Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval

Scale GP (Scale Generative AI Platform) is an enterprise-grade AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our core infrastructure in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will implement solutions across multiple cloud providers (GCP, Azure, AWS) for customers in diverse, highly-regulated industries like healthcare, telecom, finance, and retail. What You’ll Do: Architect multi-cloud systems and abstractions to allow the SGP platform to run on top of existing Cloud providers Implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Collaborate with platform, product teams and our customers directly to develop and implement innovative infrastructure that scales to meet evolving needs. Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Be able, and willing, to multi-task and learn new technologies quickly What We’re Looking For: 4+ years of full-time engineering experience, post-graduation Experience scaling products at hyper growth startups Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies Proficient in Python or Javascript/Typescript, and SQL Experience with Kubernetes Experience with major cloud providers (AWS, Azure, GCP) Excellent communication skills with the ability to explain technical concepts to both technical and non-technical audiences Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries fo

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is seeking a skilled Software Engineer with a passion for building high-performance, low-level systems software. In this role, you’ll contribute to the development and optimization of the infrastructure that powers our cutting-edge processors, with a primary focus on C/C++ development and low-level programming. You'll work closely with large inference and training model development to further drive Scale Out software and hardware performance. This role is hybrid, based out of Toronto, ON. Who You Are Strong C or C++ systems engineer with a deep understanding of memory, threading, I/O, and low-level execution models. Experienced building low-level software, drivers, embedded systems, or performance-critical infrastructure. Comfortable working close to hardware and curious about how systems behave under the hood. Proficient with Linux systems programming and debugging tools such as gdb, strace, and perf. Structured problem solver who thrives in fast-paced, highly technical environments. What We Need Design, develop, and maintain core infrastructure software that interfaces directly with Tenstorrent hardware. Build low-level libraries and APIs for communication and synchronization across compute nodes. Optimize system-level software for performance, scalability, and reliability in distributed environments. Support hardware

About the Team The Spark Platform team owns and operates DoorDash's Apache Spark ecosystem — the execution runtime, remote shuffle service, cluster scheduler, and reliability tooling that powers the company's data, analytics, and ML workloads. We run Spark across the company at significant scale and continue to expand the workloads, capabilities, and consumer base we serve. Orchestrating and operating thousands of Spark cluster deployments is a complex distributed system problem which the team invests heavily in runtime optimization, systems architecture, multi-tenant scheduling, and end-user tooling. About the Role As a Senior Software Engineer on Spark Platform, you will set the technical direction for our in-house Spark deployment and shape the architecture that will run DoorDash's data, analytics, and ML compute for the next five years and beyond. You will own the deep, cross-cutting problems that span the runtime, the shuffle service, the scheduler, and the overall service reliability — making the architectural calls that compound across the platform's lifetime. You will partner with the Engineering Manager on technical roadmap, hiring, and team shape, and act as the senior technical voice in cross-team partnerships with Data Engineering, ML Platform, and product engineering teams that depend on the platform. You must be located in San Francisco, Sunnyvale, Seattle, or New York City for this hybrid position. You will report into the Engineering Manager on our Spark Platform team. You're excited about this opportunity because you will… Set the multi-year technical direction for an in-house Spark-on-Kubernetes platform — runtime, shuffle, scheduler, reliability — and make the architectural calls that compound for years. Own the deepest distributed-systems problems on the team: shuffle architecture, multi-tenant scheduling, runtime performance, and the failure modes that only show up at scale. Partner with the Engineering Manager on technical roadmap, hiring, inte

About the Team Compute Foundations builds the software that manages OpenAI’s GPU compute infrastructure across sites, data centers, and infrastructure providers, supporting model training and inference. Our systems turn large, heterogeneous fleets of machines into dependable compute for research and products. We build Kubernetes-based control planes, controllers, services, and APIs that coordinate the lifecycle of machines and clusters. We connect global infrastructure management with the realities of bare-metal systems, giving clients consistent interfaces across differences in hardware, topology, and provider behavior. About the Role You will build distributed systems that provision, configure, and manage compute throughout its lifecycle. Your work will connect global services and Kubernetes controllers with the systems that bring machines online, update them safely, and recover them when something goes wrong. This role combines software architecture with an understanding of how machines and data centers work. You might design a lifecycle API, improve controller performance under high concurrency and provider rate limits, or trace a provisioning failure from an API through reconciliation to network boot or host configuration. You will help these systems remain reliable as the fleet expands across sites and generations of GPU hardware. We value depth in relevant systems and the ability to connect layers. You do not need to arrive as an expert in every component of the stack. In this role, you will: Design, build, and operate Kubernetes-based controllers and distributed services that coordinate infrastructure across sites, isolate failures, and scale as GPU capacity grows. Define APIs and resource models that let clients request and track lifecycle operations through consistent interfaces across hardware platforms and providers. Build provisioning and configuration services that coordinate network boot, hardware management interfaces, and the deployment of firmware,

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Our Infrastructure team is passionate about building software to solve problems at massive scale. We do this often, and when we believe our solution is worth sharing with the community, such as Envoy Proxy , we open source our ideas for the benefit of others. As a Infrastructure Engineer at Lyft, you will run our Production Infrastructure by monitoring system availability and take a holistic view of our platform health. You will build software and platforms to automate infrastructure platform operations and management. By measuring and monitoring our operations you will seek opportunities to optimize our systems in order to push our platform forward, anticipating our customers' needs in order to continually improve the platform. You will provide Lyft partner teams with operational support to help them build robust large scale distributed systems. About the Team Data Pipelines is at the heart of all critical data flowing through Lyft supporting hundreds of services that impact millions of drivers and passengers every day. Our team’s mission is to empower Lyft engineers to self-serve in building and maintaining data pipelines as needed to support products that deliver the world’s best transportation experience. We leverage a variety of technologies to store, stream and manage data making it available to our internal customers. Responsibilities: Maintain and analyze metrics from; operating systems; control planes; and applications to assist in fault detection and performance enhancement Design, develop and deploy tooling and systems that continually improve the reliability, scalability and efficiency of our platform Balance feature development speed and reliability with service-level objectives Operate and improve our Infrastructure using industry best practices and tools Participate in design and

As an Engineering Manager on Coder’s Core Workspaces 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 while growing the team and keeping 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 Workspaces 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 React and TypeScript . Experience with Go . 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. Bonus tacos if you have Experience building coding agents, developer tools, or cloud development environments. Experience with MCP , agent tools, or multi-agent systems. Experience with remote execution, sandboxing, or isolated compute. Experience building abstractions across multiple model providers. Deep experience with AWS, Kube