Ai Platform Engineer in United States

🚀 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 looking for an exceptional software engineer to join our rapidly evolving team at WRITER. In this pivotal role, you'll be at the forefront of expanding human capacity by building the next generation of AI-powered solutions that transform how leading enterprises operate. You'll dive deep into developing a state-of-the-art platform that leverages cutting-edge generative AI technologies, from large language models to sophisticated agentic workflows, delivering seamless, scalable, and secure applications that redefine enterprise productivity. This is an unparalleled opportunity to make a tangible impact, shaping the future of AI and contributing to a product that’s changing how the world works. This role is hybrid, based out of our San Francisco, New York City, or Seattle hubs. You'll report to our senior director, engineering . 🦸🏻‍♀️ What you’ll do Design and deliver secure, scalable AI integration platforms that connect enterprise systems and power missio

🚀 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 At WRITER, our mission to expand human capacity with superintelligence relies on a foundational truth: our platform must be available, performant, and reliable, 24/7. As an Infrastructure engineer, you'll be at the heart of making this a reality, impacting every enterprise customer who trusts us with their AI-powered workflows. This isn't just about keeping the lights on; it's about pushing the boundaries of what's possible, proactively identifying and solving complex systemic challenges, and laying the groundwork for our rapid growth and the evolving demands of enterprise generative AI. You'll build resilient systems, automate across the stack, and champion reliability best practices, directly enabling our ambitious product roadmap and ensuring our customers always have access to the powerful tools they need. This is a hybrid position, based out of our New York City, San Francisco, Seattle, or London hubs. You'll report to our director of engineering. 🦸🏻‍♀️

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. With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Driver, Marketplace, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing petabyte-scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. The Fulfillment group, within the Marketplace at Lyft, is responsible for determining what inventory can be reliably offered for a given rider session and fulfilling rider requests. The group comprises several sub-teams that generate feasible offers for riders, match rider requests with drivers, and maintain a distributed state machine to track rides and drivers from request through completion. We are seeking a Machine Learning Engineer to join the Fulfillment team and lead the design, development, and deployment of state-of-the-art machine learning systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging machine learning and data science. Responsibilities: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions Design and implement feature pipelines, model training workflows, and serving infrastructure using Lyft's ML platform Evaluate ML system performance against business KPIs, run experiments, and drive continuous model improvement

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. Vanta's App Primitives team owns the shared building blocks that span data structures to UI: comments, notifications, event logs, feature flags, and task management. We own the general infrastructure; product teams own the logic built on top. Getting this layer right unlocks velocity for every team at Vanta. As the Engineering Manager, App Primitives at Vanta, you'll lead the team building the shared product primitives that every Vanta product team depends on, owning the infrastructure layer that makes collaboration, communication, and core workflows possible across the entire platform. Our Engineering Managers develop and grow high-performing teams that deliver significant value to our customers and enable our business to scale. This role sits at the intersection of technical architecture and team development, with real authority to set direction and grow a world-class platform team. Visit our Vanta Engineering Blog to learn more about what our team is working on! What you’ll do as an Engineering Manager at Vanta: Lead and grow the App Primitives team, owning hiring, team health, delivery, and the development of senior engineers and technical leads Own the strategy and roadmap for Vanta's shared product primitives: comments infrastructure, notifications platform, event log, feature flag system (Statsig), and task management Define and steward the interface model between App Primitives systems and product teams, ensuring product teams can build on top of shared infrastructure quickly and safely, without owning the underlying systems themselves Partner closely with product engineering leaders across Vanta to surface developer ne

Senior Security Engineer, Vulnerability Management Here at Datadog, we think about vulnerability management a little differently. We embrace open source software, recognize our role in the software supply chain, and see attackers weaponizing vulnerabilities faster than ever. We are looking for a Senior Security Engineer who can combine vulnerability-management judgment with hands-on engineering to help us scale and improve our vulnerability lifecycle across Datadog’s multi-cloud products and services. In this role, you will turn ambiguous security problems into clear solutions, and work with engineering teams to address root causes and develop technical controls that reduce vulnerabilities earlier in the SDLC. You’ll use AI and automation to help scale the overall vulnerability lifecycle across Datadog. You will use data and sound technical judgment to prioritize risk, and partner with security, product, platform, and compliance teams to bring scalable solutions into practice. At Datadog, we place value in our office culture - the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do Work across the vulnerability lifecycle from detection and impact assessment through risk-based prioritization, remediation, and verification. Use AI and automation to build tools, services, and workflows that make security ideas concrete, validate them quickly, and create alignment for scalable implementation. Reduce engineering toil through a “PRs, not tickets” approach, using automation to enrich findings, identify ownership, recommend or deliver fixes, and track outcomes. Analyze recurring vulnerabilities and remediation failures to identify root causes and opportunities to prevent issues earlier in the SDLC. Partner with SDLC Security, Product Security, platform teams, and engineering teams to balance technical constraints, busin

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We embed deeply with users to solve high-leverage problems. We move quickly from prototype to deployment and surface patterns that shape the platform. We operate at the intersection of customer delivery and core development. We work closely with Product, Research, and Go-To-Market (GTM). About the role We are hiring a Forward Deployed Engineer (FDE) to build and deploy AI systems for legal work. You will embed deeply with customers—often working closely with senior legal practitioners—to identify the right first use case, rapidly prototype a solution, and prove measurable value. Early engagements may focus on creating a “hero” workflow that shows how OpenAI’s models can support legal analysis, drafting, research, or real-time work with complex case records. You will own the technical work from discovery and proof of concept through production adoption, while translating customer workflows and constraints into clear product feedback. As the motion matures, you will turn successful deployments into repeatable patterns that can scale across larger accounts and the broader legal market. This role is based in San Francisco or New York City. We use a hybrid work model of three days in the office per week and offer relocation assistance. Travel up to 50% may be required. In this role, you will Embed with law firms and legal teams to understand their workflows, identify high-value opportunities, and select the right initial use cases to prove value. Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks t

About the Team The Consumer Devices team at OpenAI builds end-to-end hardware and software systems that bring AI into the physical world. We work at the intersection of custom silicon, embedded systems, operating systems, and cloud services to deliver reliable, production-ready devices at scale. About the role We are looking for an Operating Systems Engineer to build and harden the OS foundations for OpenAI products. We are especially interested in experienced, passionate, and innovative operating systems developers who thrive on building foundational platform software and solving hard problems in security, privacy, performance, power, and reliability. You will work across the OS kernel, core OS services, security and privacy primitives, performance and power, and the frameworks that connect applications and UI to the system. This role emphasizes deep debugging and systems ownership from development through production. You will collaborate closely with embedded, firmware, hardware, application, and product engineering teams. Experience with hardware bring-up is a plus, but not required. What you will do Work on end-to-end OS capabilities spanning the OS kernel, userspace services, application frameworks, UI toolkits, and application-facing APIs. Develop, integrate, and maintain OS components, both kernel-bound and in userspace, including scheduling, memory management, filesystems, drivers, IPC/RPC mechanisms, and security-relevant subsystems. Build and maintain core OS services and daemons (init, service management, device discovery, networking primitives, time, logging, update hooks, crash handling, and so on). Design and implement security and privacy mechanisms: Secure boot and measured boot integration points (where applicable). Mandatory access control and sandboxing. Secrets management, secure storage, key handling, and least-privilege service design. Privacy-preserving telemetry, data minimization, and user-consent oriented system behaviors. Establish a perfo

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We embed deeply with users to solve high-leverage problems. We move quickly from prototype to deployment and surface patterns that shape the platform. We operate at the intersection of customer delivery and core development. We work closely with Product, Research, and Go-To-Market (GTM). About the role We are hiring a Forward Deployed Engineer (FDE) to build and deploy AI systems for legal work. You will embed deeply with customers—often working closely with senior legal practitioners—to identify the right first use case, rapidly prototype a solution, and prove measurable value. Early engagements may focus on creating a “hero” workflow that shows how OpenAI’s models can support legal analysis, drafting, research, or real-time work with complex case records. You will own the technical work from discovery and proof of concept through production adoption, while translating customer workflows and constraints into clear product feedback. As the motion matures, you will turn successful deployments into repeatable patterns that can scale across larger accounts and the broader legal market. This role is based in San Francisco or New York City. We use a hybrid work model of three days in the office per week and offer relocation assistance. Travel up to 50% may be required. In this role, you will Embed with law firms and legal teams to understand their workflows, identify high-value opportunities, and select the right initial use cases to prove value. Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks t

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Software Engineer II Overview Join a team focused on transforming how Mastercard's payment systems are built, scaled, and operated. As a Software Engineer II, you will design and develop cloud-ready applications, microservices, and APIs that support large-scale payment processing platforms while helping advance modernization, automation, and engineering excellence across the organization. You'll work on scalable backend systems, contribute to platform modernization initiatives, and collaborate with engineers to deliver reliable software solutions. This role is ideal for someone who enjoys solving technical challenges, building production-ready applications, and continuously improving how software is designed, developed, tested, and supported. What You Will Do •Design software components by translating product requirements into scalable technical solutions. •Contribute to software architecture decisions and technical design discussions. •Build modular, extensible, maintainable, and performant applications. •Design, execute, and maintain unit, functional, and integration tests. •Apply secure coding practices throughout the software development lifecycle. •Participate in code reviews and contribute to engineering quality standards. •Support system performance optimization, scalability impr

We are looking for a 100% hands-on Storage Services Software engineer to join the block storage group. You will be a member of a team that builds the next-generation block storage capabilities and architects a proprietary distributed file system solution from its inception. You will work closely with a variety of teams and architects including the networking team, and external customers. You will take part in defining the software architecture and implementation of the most advanced storage services! Services that will need to meet extreme performance and scalability demands! We have crafted a team of extraordinary people stretching around the globe, whose mission is to push the frontiers of what is possible today and define the platform of tomorrow. At NVIDIA, we work, think and learn as a team. We thrive in a deeply strong environment, and we're passionate about a culture that demands innovation and the highest standards. The rewards are sweet and include collaborating with some of the smartest people in the industry, an aggressive compensation plan that rewards top performers, and the opportunity to work on products that transform the way people work and play. What you’ll be doing: 100% hands-on coding role in C language, Kernel and Userspace Access advanced AI tools and a token budget for code development provided by NVIDIA, the world's AI factory leader. Research, design, implement and test, new and existing, distributed storage services and features of NVIDIA’s block and file storage solution, in both Host and DPU environments. Acquire understanding of the algorithms, the technicalities and the interaction with other components across NVIDIA’s block and file storage ecosystem. Analyze and solve challenging bugs and customer cases in la

We're looking for a Principal Engineer to join our CSP Engagements team as the technical focal point for end-to-end performance, working directly with engineering teams of key CSP/hyperscale customers to ensure they achieve various performance targets on NVIDIA platforms. In this role, you will augment NVIDIA's performance and benchmark teams with a dedicated CSP-facing focus. You will drive work streams with CSP engineering teams to build shared understanding of platform performance characteristics, gather and incorporate their workload-specific feedback into NVIDIA's optimization priorities, and validate that performance targets are met in customer-representative configurations. Your cross-CSP visibility enables you to identify patterns and drive systemic improvements in documentation, configuration guidance, and tooling. What you'll be doing: Drive performance characterization work streams with engineering teams of key CSP/hyperscale customers — ensuring they understand platform performance expectations, profiling methodology, and tuning options for their specific workloads Gather and synthesize CSP performance feedback — identify gaps between expected and actual throughput, and champion optimization priorities back into NVIDIA's CUDA, NCCL, driver, and firmware teams Ensure key open-source performance and stress tools (e.g., STREAM, GPU Burn, GPU BLAST) are updated and validated for the latest NVIDIA rack-scale systems, GPU architectures, and CPU platforms — so customers and internal teams have reliable baseline measurements from day one Work closely with CSPs to ensure their own performance and validation tooling reflects the latest GPU capabilities, memory hierarchy changes, and platform-specific tuning parameters Conduct cross-CSP performance comparison and pattern analysis — identify configuration, software, or workload differences that explai

Become a part of our caring community Humana is seeking a self-driven and collaborative Lead Engineer to join our Interactive Voice Response (IVR) team. In this role, you will deliver innovative IVR solutions and develop robust omnichannel APIs for our enterprise platforms. You will have the opportunity to drive the success of a high-impact, customer-facing application within a Fortune 50 company, working closely with multiple teams throughout the software development lifecycle (SDLC). Lead Engineer –Omnichannel Humana is seeking a self-driven and collaborative Lead Engineer to join our Omnichannel team. In this role, you will design, develop, secure, and enhance enterprise APIs that support high-impact, member facing, applications across Humana's digital and voice channels. This role offers the opportunity to modernize and strengthen existing API capabilities while helping deliver resilient, scalable, and secure omnichannel solutions within a Fortune 50 organization. Key Responsibilities Design, develop, and maintain scalable Omnichannel APIs that support enterprise applications and customer-facing capabilities. Enhance the security, resiliency, performance, and reliability of existing APIs through modernization, improved architecture, observability, testing, and operational controls. Apply AI and AI-assisted engineering practices to accelerate development, improve quality, automate testing, enhance documentation, and identify opportunities for optimization. Partner with architecture, security, cloud, product, engineering, and operations teams to deliver secure, resilient, and enterprise-aligned API solutions. Collaborate with agile teams to plan, track, and deliver API enhancements, platform improvements, and cloud-based capabilities. Develop proofs of

About PostHog Product development used to mean manually writing code, running analysis, diagnosing bugs, and rolling out changes using dozens of tools. PostHog is the only platform that acts like a co-pilot for you (and your AI agents) to do it all – autonomously. We started with open-source product analytics, launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products , including: PostHog Code , the only AI devtool that understands your product, not just your codebase. A built-in data warehouse , so users can query product and customer data together using custom SQL insights. PostHog AI , an AI-powered analyst that answers product questions, helps users find useful session recordings, and writes custom SQL queries. We are: Product-led . More than 450,000 organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change when needed. Shipping fast: Why not n

We are developing advanced multi-rack, multi-tenant AI/ML datacenters with NVIDIA GB200, and upcoming GB300 GPUs. NVIDIA seeks a Senior Software Engineer for our CSP (Cloud Service Provider) Engagements team to focus on the cloud-native stack for datacenter products like GB200. In this role, You will define customer workflows, prototype stack enhancements, and debug the toughest Kubernetes + Slurm issues in multi-rack, multi-tenant AI datacenters. You'll tackle complex scheduling challenges across racks, tenants, and clouds as part of the CSP engagements team. What you’ll be doing: Perform deep-dive debugging of multi-rack, multi-tenant clusters: scheduler behavior, container runtime issues, device-plugin crashes, RDMA/IB fabric anomalies, etc. Gather customer requirements and prototype feature extensions for Kubernetes operators, Slurm plugins, and custom micro-services that expose new GPU capabilities. Drive joint architecture reviews and “whiteboard” sessions with CSP and internal platform teams; convert findings into RFCs and upstream pull requests. Create reproducible testbeds (Helm/Ansible/Terraform) that mirror customer environments; automate validation and benchmark suites. Deliver technical collateral-design docs, how-to guides, demo scripts-and present at customer on-sites, KubeCon, and SlurmUG. Collaborate with AE, FAE, and Solution Architect teams to deliver integrated customer solutions and technical documentation. What we need to see: Strong source-level expertise in Kubernetes internals (scheduler, CRI/CNI/CSI, operators) and Slurm (federation, power-save, plugins). Hands-on experience integrating next-gen GPUs (Blackwell/GB200/GB300) or comparable accelerators into containerized clusters. Proven track record debugging large-scale, cloud-native stacks across ne

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. Role Overview We are seeking an experienced ASIC Package Signal Integrity / Power Integrity Engineer to drive electrical architecture, modeling, optimization, and validation for the most advanced AI/HPC silicon and package design. This role focuses on high-speed SerDes and memory channel architecture, advanced 2.5D/3D package SI/PI, substrate to package co-design, power-delivery-network optimization, electromagnetic modeling, and simulation-to-measurement correlation. The ideal candidate has strong hands-on experience with high-speed channel and PDN analysis across ASIC packages, interposers, substrates, and power-delivery structures, and can translate simulation results into practical design requirements for interposers and package substrate design optimization. The engineer will work closely with ASIC, package, system, mechanical, thermal, power, and silicon validation teams from early architecture and feasibility studies through production bring-up. In this role you will Own SI/PI architecture and analysis for advanced AI ASIC packages from early feasibility studies through production. Develop and optimize high-speed electrical channels for 200G/400G SerDes, PCIe, HBM, DDR, and chiplet/die-to-die interfaces. Perform package, interposer and substrate modeling using 2D/3D electromagnetic solvers. Define and optimize package stack-ups, transmission-line structures, via transitions, breakout structures, return paths, ground shielding, bump maps, and ball maps based on SI/PI re