Software Engineer Distributed Systems Jobs

Staff Software Engineer - Platform Location: Soho, NYC / Remote Department: Engineering The Role We’re looking for a Staff Software Engineer to help grow and build the core platform that powers our Flowcode 2 application at scale. This role sits at the intersection of architecture, leadership, and pragmatic execution with a focus on creating and augmenting reliable, scalable, and extensible services and applications. You’ll operate as a technical leader with in our Platform pod, growing platform capabilities, building new features and problem solving in a dynamic and challenging technical environment.. While this is a hands-on role, it requires a strong bias toward backend systems, distributed architecture and deep technical leadership. We value the ability to guide teams toward pragmatic, high-impact solutions. This role is ideal for an engineer who values simplicity, correctness, and pragmatism, and who can balance long-term platform investments with immediate business needs. What You’ll Do Own critical systems end-to-end, including design, implementation and deployment, Hands on designing, building, and maintaining scalable features across a modern front-end framework and backend services. Architect for growth — help drive your pods’s technical roadmap and shepherd established engineering best practices. Collaborate across teams with product, design, and data to deliver measure, deliver and grows features quickly and iteratively. Mentor and guide senior engineers, raising the bar for technical execution and system design across teams. Balance ideal engineering with the realities of speed, customer needs, and startup resource constraints. Drive improvements in observability, performance, and incident response Advocate for pragmatic solutions, solving the right problems with the appropriate level of complexity. What We’re Looking For 8+ years of experience building and operating production-grade systems, with a strong backend focus. Deep expertise in building

About the Role We are a small team of AI builders in Paytm Labs. As a Staff AI Platform Engineer, you will work across inference and agentic systems. You will contribute to Paytm's AI inference platform (Pi), serving internal teams and enterprise customers - running our own coding and domain-specific models (voice, vision, risk, fintech workflows) as well as third-party models. You will also architect and build the platform that enables autonomous AI agents to operate safely and reliably in production - the runtime, orchestration, and developer tooling for agents to reason, plan, use tools, and execute complex multi-step workflows, automating both software development and business processes. You will work at the intersection of LLMs, distributed systems, and production fintech infrastructure, helping define how inference and agentic AI are built and deployed across payments, risk, fraud, collections, support, and developer experience. What You'll Do Inference & Model Serving Build and operate multi-model serving across modalities (text, voice, code, vision) on shared infrastructure Own the model lifecycle: download, deploy, serve, monitor, update, swap Drive inference optimization: latency, throughput, cost - including quantization, batching, caching, and routing strategies Ensure inference is fast and reliable for the agents and systems that depend on it Agentic Systems Architect and build the Agentic AI Platform - runtime infrastructure, orchestration systems, and developer tooling for autonomous agents Design multi-agent coordination systems enabling agents to collaborate and solve complex workflows Build robust tool-use infrastructure that allows agents to interact with APIs, databases, and services safely Implement workflow automation: agents that execute multi-step business and engineering tasks with appropriate guardrails Build safety and gu

About SingleStore SingleStore delivers a real-time, distributed SQL database that unifies transactional and analytical workloads. Our engineers build cloud-native software for some of the world’s most demanding data-intensive applications, working in a fast-moving environment where teams own their work end to end and partner closely across Product and customer-facing organisations. About the Flow team SingleStore Flow is an enterprise data migration and integration product that helps customers move data into SingleStore reliably and at scale. The team builds the systems that support schema transfer, bulk data loading, real-time Change Data Capture (CDC), large-table migrations, and a native experience in SingleStore Helios. Flow spans Java-based engines, source and destination connectors, database internals, performance and memory management, Helios services and APIs, observability, test automation, Flow AI Agent and signed production release delivery. The product works across heterogeneous database environments, including MySQL, PostgreSQL, Oracle, SQL Server, MongoDB, SAP HANA, Snowflake, Salesforce, and SingleStore-as-a-source. Position Overview We are looking for a Staff Engineer to provide technical leadership for Flow’s end-to-end data path from source systems and CDC through migration engines, APIs, Helios, and the customer experience. This is a hands-on individual contributor role with broad technical influence. You will own major architectural decisions, lead strategically important and release-defining initiatives, solve complex reliability and data-consistency problems, and help the team build durable systems that customers can trust with their most important migrations. You will remain close to the code while raising the technical bar for design, testing, observability, operational excellence, and AI-assisted engineering. The ideal candidate is a systems-minded engineer who enjoys working across product boundaries, can move comfortably between architectu

The MongoDB Customer Observability Team is a diverse group of contributors working together to help our users manage MongoDB at global scale. The team is responsible for MongoDB Atlas: our database-as-a-service offering and fastest-growing product, which allows users to deploy globally distributed MongoDB clusters in just minutes. We're seeking an SE3 to join our team to tackle exciting challenges within the Observability space. You'll contribute to developing tools and platforms that help our users understand the health and performance of their MongoDB deployments. This includes collecting metrics, monitoring slow queries, and offering actionable insights such as index and schema suggestions that improve the speed, efficiency, and overall reliability of their databases. This role provides a unique opportunity to drive engineering excellence across both dimensions of observability, leveraging technologies being developed within the Customer Observability group and contributing directly to the success of our customers and our product teams. If you're passionate about large-scale systems, digging deep into telemetry data, and building tools that make a real impact both internally and externally, we’d love to have you on board! We are looking to speak to candidates who are based in Dublin for our hybrid working model. We're looking for someone who Enjoys collaboration and being part of a team Is approachable, curious, and intellectually honest Is a backend engineer with a willingness to take on frontend tasks or a full-stack developer with a bias towards backend Has written backend systems in a compiled language (Java, C#, Go, etc.) Has experience with the design and architecture of a modern, scalable web application Is familiar with debugging and troubleshooting production issues Strong understanding of algorithms, data structures and their time and space complexity Nice to Haves Experience developing and writing code observability tools Previous work in T

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 is seeking Software Engineers to join our Observability team within the Infrastructure organization. The Observability team owns the monitoring and telemetry infrastructure that every engineer and researcher at Anthropic depends on—from metrics and logging pipelines to distributed tracing, profiling, error analytics, alerting, and the dashboards and query interfaces that make it all actionable. By joining this team, you'll have a direct impact on the reliability and operational excellence of Anthropic's research and product systems. As Anthropic scales its infrastructure across massive GPU, TPU, and Trainium clusters, the volume and complexity of operational data is growing by orders of magnitude—and an increasing share of the hardest problems live below the application layer. We're building next-generation observability systems—high-throughput telemetry pipelines, fleet-wide continuous profiling, eBPF-based tracing and network visibility, and agentic diagnostic tools—so engineers can detect, diagnose, and resolve issues in minutes rather than hours, even when the answer lies in the kernel, the network stack, or an accelerator rather than on a dashboard. Key responsibilities Design and build scalable telemetry ingest and storage pipelines for metrics, logs, traces, and error data across Anthropic's multi-cluster infrastructure Build observability solutions that give engineers deep, low-overhead visibility into system behavior across the fleet Own and evolve core observability platforms, driving migrations and architectural improvements that improve reliability, reduce cost, and scale with organizational growth

Join the MongoDB Server Query team, and help us build a world-class distributed open source query engine. 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, from parsing to optimization to plan selection and finally execution. This also includes our geospatial search and update subsystems. Our global team is growing fast. In North America, we have a presence across the US and Canada including New York, West Coast, Toronto. In Europe, we have a presence in Dublin, Germany, France, Netherlands, UK, Bulgaria, Spain and Italy currently. We support office-based and remote work and align projects with convenient work hours for each time-zone. We have tons of interesting problems to solve with direct impact on users for transactional, time-series and analytical workloads. We need your help to design and build the heart of a distributed, flexible schema, document database. We are looking to speak to candidates who are based in Dublin or Cork for our hybrid working model. Candidate Profile 3+ years of experience in data intensive environments 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 B.Sc in Computer Science or similar field, or equivalent practical experience Experience in C++ and in developing database systems is a plus Interest in the theory and practice of database query engines. Hands-on experience or M.Sc./Ph.D in the domain is a plus Position Expectations Understand and improve current functionality of the MongoDB query engine 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 with other engineers to

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role As a software engineer on the Scaling team, you’ll help build and optimize the low-level stack that orchestrates computation and data movement across OpenAI’s supercomputing clusters. Your work will involve designing high-performance runtimes, building custom kernels, contributing to compiler infrastructure, and developing scalable simulation systems to validate and optimize distributed training workloads. You will work at the intersection of systems programming, ML infrastructure, and high-performance computing, helping to create both ergonomic developer APIs and highly efficient runtime systems. This means balancing ease of use and introspection with the need for stability and performance on our evolving hardware fleet. This role is based in San Francisco, CA, with a hybrid work model (3 days/week in-office). Relocation assistance is available. In this role, you will: Design and build APIs and runtime components to orchestrate computation and data movement across heterogeneous ML workloads. Contribute to compiler infrastructure, including the development of optimizations and compiler passes to support evolving hardware. Engineer and optimize compute and data kernels, ensuring correctness, high performance, and portability across simulation and production environments. Profile and optimize system bottlenecks, especially around I/O, memory hierarchy, and interconnects, at both local and distributed scales. Develop simulation infrastructure to validate runtime b

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 Software Engineer on Spark Platform, you will execute across the surfaces of our in-house Spark deployment that serves the entire company. The work spans Spark runtime upgrades and performance, multi-tenant scheduling and executor bin-packing on Kubernetes, cluster lifecycle automation, and the observability and incident automation that keep the platform sustainable. You will move between layers as the work demands — picking up the next high-leverage problem regardless of where it sits — and partner closely with the rest of the team and with platform consumers across the company. 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… Build and operate an in-house Spark platform that runs at company-wide scale, spanning runtime, scheduler, reliability, and user-facing tooling. Drive multi-tenant scheduling, executor bin-packing, and cost-aware placement that let a small team serve dozens of consumer teams. Own pieces of cluster lifecycle automation — provisioning, upgrades, capacity changes, and node-failure handling — at a scale where these stop being manual events. Build the observability and incident automation that make the platform debuggable end-to-end and keep on-call sus

We are a global team of innovators and pioneers dedicated to shaping the future of observability. At New Relic, we build an intelligent platform that empowers companies to thrive in an AI-first world by giving them unparalleled insight into their complex systems. As we continue to expand our global footprint, we're looking for passionate people to join our mission. If you're ready to help the world's best companies optimize their digital applications, we invite you to explore a career with us! Your opportunity The Data, Identity, & API Platform group at New Relic builds the foundation for all of our products: data ingest, storage, and query. As an engineer working on NRDB, you’ll be contributing directly to the proprietary telemetry database technology at the core of our business. We own our software from top to bottom and are directly responsible for its quality and reliability. Each member of the team shares our pager rotation and will occasionally be on-call to respond to system failures; so we prioritize work that keeps the lights on and the pager quiet, in addition to the work that powers all of our new products and streams of data. If the idea of working on systems that process millions of messages per second and handle petabytes of data excites you, then you may be an excellent fit! What you'll do Own the New Relic query gateway stack Proactively participate in cross-functional committees to move the query gateway forward, ranging from collaborations with AI, Visualizations, and Data Processing teams. Build and maintain scalable distributed Java services and Petabyte-scale Infrastructure. Investigate and resolve critical performance, availability, and resiliency issues and risks in a multi-region, multi-cloud, multi-tenant distributed database. Working in an agile environment with a DevOps approach — the team builds and maintains their own software, including taking turns with being on-call. This role requires 3+ years of experience in collaborativ

Company: tastytrade Role: Software Engineer (Ruby) Location: Chicago, IL — Hybrid Salary: $130,000-$150,000 As a Software Engineer you will be part of a team that builds out the technology powering our retail brokerage business and supporting our other business initiatives. We care about the speed and stability of our back-end systems as much as we care about the customer-facing applications we build. Our architecture is distributed and consistently evolving as our business grows and we face different technical challenges, but always with a focus on practicality and performance. You'll help by modifying existing systems, taking ownership of current systems as well as green field projects, and troubleshooting issues as they arise. Our engineers work with a plethora of tools including Java, Javascript, and Ruby. You'll work primarily in Ruby but will have opportunities to expand your skill set into areas where your interests and our technology intersect. Ruby doesn't have to be your primary language today. If you're strong in another object-oriented language — Java, for example — and you're genuinely keen to make Ruby your day-to-day, we'd like to hear from you. Our technical interview is conducted in Ruby wherever possible, so you'd need to be comfortable enough to code in it by the time we meet. What You'll Do Work in multiple languages across different parts of the tastytrade stack and/or front-end trading client applications. Design, build and maintain services in a distributed architecture, thinking about failure modes, latency and data consistency as you go. Provide guidance and leadership to more junior members of the team when questions arise about language or implementation specifics, and contribute in a meaningful way to our peer review process. Translate requirements and technical direction into production-quality code with lightweight guidance from a senior engin

The Collision Avoidance System (CAS) is responsible for detecting and reacting to imminent collision situations in support of our vehicle’s overall safety goals. CAS Perception is responsible for processing raw sensor data from our vehicle’s world-class sensor suite using a combination of geometric, interpretable algorithms and deep learning to detect near-collisions with obstacles along our intended driving path, in the most challenging dense urban environments and under tight compute resource constraints. Overall CAS is parallel and complementary to our Main Artificial Intelligence (AI) autonomy stack, and has a close relationship with our vehicle hardware and safety teams in order to architect redundancy into our overall driving system. The CAS Verification & Validation (CAS V&V) is a multidisciplinary team data, software and systems engineers defining and building metrics to measure the Collision Avoidance System performance and work with the Systems Design and Mission Assurance (SDMA) and QA teams to develop validation plans for the features. In this role, you will: Apply distributed computing algorithms to analyze petabytes of urban driving data. Develop metrics and tools to analyze errors and system improvements. Work closely with CAS engineers to evaluate system performance. Collaborate with Perception engineers to define metrics for autonomous driving. Partner with Planning engineers to measure performance in complex urban environments. Qualifications: BS, MS, or PhD degree in computer science or a related field Fluency in C++ and/or Python Extensive experience with programming and algorithm design Bonus Qualifications: Experience with analysis of latency for safety-critical software systems Experience with petabyte-scale distributed computing (Spark, Databricks, generic MapReduce pipelines) <li

OpenAI’s charter calls on us to ensure the benefits of AI are distributed broadly and safely. Our Health AI team focuses on expanding access to high-quality medical expertise and aims to set a high standard for deploying AI responsibly in high-stakes domains. Improving health will be one of the defining impacts of AGI. Today, millions of people lack access to reliable medical information, and clinicians around the world face increasing time and resource constraints. We are building AI systems that support patients, clinicians, and health workers, while meeting the highest standards for safety, reliability, and privacy. We are seeking full stack software engineers to help build and scale products used by consumers and care providers globally. You will work closely with product, design, and research teams to ship real systems in a fast-moving, high-impact environment. In this role, you will: Design and build scalable fullstack systems for consumer and enterprise health. Own end-to-end feature development—from early design and implementation through deployment, monitoring, and iteration. Build and maintain data pipelines and services that meet strict privacy, security, and compliance requirements (e.g., HIPAA). Collaborate closely with researchers and safety teams to integrate reliability, evaluation, and guardrails into production systems. Debug, optimize, and harden systems to support high availability, performance, and global scale. Take ownership of ambiguous problems and drive them to practical, high-quality solutions. You might thrive in this role if you: Are deeply motivated by improving health outcomes and expanding access to medical expertise. Are a strong engineer who enjoys building durable, well-designed systems. Have 5+ years of experience writing maintainable, production-quality code. Can operate with high agency—owning problems end-to-end with minimal supervision. Enjoy working in fast-moving, cross-functional teams with engineers, product managers, desi

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 Software Engineer on Spark Platform, you will execute across the surfaces of our in-house Spark deployment that serves the entire company. The work spans Spark runtime upgrades and performance, multi-tenant scheduling and executor bin-packing on Kubernetes, cluster lifecycle automation, and the observability and incident automation that keep the platform sustainable. You will move between layers as the work demands — picking up the next high-leverage problem regardless of where it sits — and partner closely with the rest of the team and with platform consumers across the company. 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… Build and operate an in-house Spark platform that runs at company-wide scale, spanning runtime, scheduler, reliability, and user-facing tooling. Drive multi-tenant scheduling, executor bin-packing, and cost-aware placement that let a small team serve dozens of consumer teams. Own pieces of cluster lifecycle automation — provisioning, upgrades, capacity changes, and node-failure handling — at a scale where these stop being manual events. Build the observability and incident automation that make the platform debuggable end-to-end and keep on-call sus

About the Team The Monetization team is a new cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products—including next-generation ads experiences—that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to help build the machine learning infrastructure that powers OpenAI’s monetization and ads systems. In this foundational role, you’ll design and develop the platform layer that enables teams to build, train, deploy, serve, monitor, and continuously improve machine learning models used across advertising and monetization products. You’ll work across the full ML lifecycle, from large-scale data pipelines and feature infrastructure to training systems, model serving, experimentation platforms, and monitoring frameworks. The systems you build will support high-throughput, low-latency advertising workloads while maintaining strict standards for reliability, privacy, security, and performance. This role sits at the intersection of machine learning systems, distributed infrastructure, and monetization, offering the opportunity to shape the core platforms that help translate model innovation into m