Platform Deployment Management Lead in United States

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Senior Software Engineer — Cortex Training The Snowflake ML Platform team's mission is to let customers run their most demanding ML/AI workloads inside Snowflake. Cortex Training is our LLM post-training platform: it turns scarce, expensive GPU capacity into a simple, composable service, so customers can adapt open-weight foundation models to their own business problems while we handle the hard distributed-systems parts, including scheduling, orchestration, multi-node training and inference, fault tolerance, and throughput. The platform already runs post-training at scale. Under the hood, it decouples GPU computation from the training loop and exposes it as primitive APIs that compose into everything from SFT to full RL workflows. You'll work alongside a team that ships fast & sweats reliability and the researchers behind DeepSpeed. We're looking for an engineer who thrives in the ML infrastructure layer and brings a solid understanding of LLMs and post-training to help us scale and grow it. YOU WILL: Design and build across the full stack — from the public training APIs and SDK through the control plane to the GPU data plane. Scale the distributed systems that make GPU compute serverless — multi-tenant scheduling, placement, and capacity-aware routing across regional G

About the Team OpenAI’s Client Platform Engineering (CPE) team delivers trusted devices at scale: secure by default, reliable by design, and effortless to use. We own platform capabilities across macOS, Windows, iOS, Android, and Linux, spanning endpoint posture and device trust, application delivery, onboarding, updates, telemetry, workflow orchestration, and employee-facing remediation. The team partners deeply with Security, Research, Applied, and specialized engineering groups to enable and protect OpenAI while reducing friction for the people advancing our mission. About the Role As an Engineering Manager for CPE, you will lead a team of engineers responsible for the strategy, delivery, and operation of OpenAI’s cross-platform client foundation. You will combine people leadership with strong technical judgment: setting direction, developing engineers, reviewing architecture and tradeoffs, and creating the operating mechanisms that turn ambiguous needs into durable platform outcomes. This is a high-leverage role at the intersection of security, reliability, developer velocity, and employee experience. CPE is a highly technical platform engineering organization delivering first-party services, automation, observability, and safe fleet operations. We’re looking for a leader who can guide its next chapter, scaling the team and its systems, partnering across the company, and raising the bar for secure, reliable, low-friction experiences across every supported platform. In this role, you will: Lead and develop a high-performing engineering team; hire thoughtfully, coach engineers, create clarity, and foster an inclusive, high-accountability culture that pushes perceived limits. Define and execute a multi-year client-platform strategy and roadmap across macOS, Windows, iOS, Android, and Linux, including how Codex and agents can reshape employee computing. Provide technical direction for endpoint posture, device trust, application delivery, device onboarding, updates,

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary Health100 is America's trusted front door to health and care. The Health100 platform integrates any participating health plan, PBM, pharmacy (retail and specialty), provider, digital health point solution provider, and employer, and addresses the top health care challenges for the consumer. We are looking for a hands-on, passionate engineering leader to join a high-energy, mission-driven team on the forefront of digital health innovation — reinventing how consumers engage with their health. As the Lead Director of Software Engineering, you will lead the strategic vision, development, and execution of our platform engineering roadmap. You will drive innovation, manage cross-functional teams, and ensure the delivery of high-quality products that exceed consumer expectations. As a key strategic leader, you will own integration strategy and execution across multiple domains, managing partner requirements, technical constraints, and external commitments while advancing platform modernization initiatives. You will partner closely with external stakeholders, understand their technical constraints and success criteria, and communicate risks and feasibility clearly in both technical and business terms. Responsibilities: </

About Datadog: We're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale—trillions of data points per day—allowing for seamless collaboration and problem-solving among Dev, Ops and Security teams globally for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Team: The Revenue Data Engineering Teams designs, builds and runs the data pipelines and helper systems to accurately and in a timely manner quantify our customers’ usage across all Datadog products. This team is at the leading edge of any new product we release. The Revenue Data Processing team builds and operates the data pipelines that does billing, and cost attribution for all Datadog products. We process terabytes of data daily to power revenue-critical systems and are at the center of every new product launch at Datadog. As a Senior Software Engineer, you will own meaningful parts of a large-scale, mission-critical processing platform — driving architectural improvements, building new billing capabilities, and maintaining the high reliability bar our downstream consumers depend on. You Will: Design and build high-throughput data pipelines for billing and cost attribution Drive platform improvements — latency reduction, Spark optimization, sharding, and cross-datacenter reliability Own root-cause investigations on billing accuracy issues in collaboration with Finance and Product teams Contribute to new billing features Work across Python and Scala, with technologies including Spark, Airflow, Trino, and Apache Iceberg Participate in on-call rotation and maintain a high reliability bar for production systems Contribute to engineering standards and help grow the technical culture of the team You Are: You have significant experience building and operating production data pipelines at scale using Spark and Airflow

About the team The Monetization Data Platform team builds the trusted data and platform foundations that power how the company develops, measures, and improves monetization products. We bring together product usage, pricing, billing, ads, payments, and financial data to help Product, Engineering, Finance, and GTM teams make better decisions and deliver reliable customer experiences. We work at the intersection of data engineering, product engineering, platform engineering, Finance, and GTM. Our goal is to turn complex monetization and financial data into accurate, explainable, and timely data products while building systems that scale with the growth and complexity of the business. About the role We are looking for a Data Engineer to improve and build the next generation of our monetization data platform. You will own high-impact systems end to end, from product instrumentation, source ingestion, and canonical modeling through quality controls, observability, and delivery to downstream consumers. This is a hands-on role for an engineer who enjoys solving ambiguous product and data problems, designing durable architectures, and partnering closely with Product Engineering, Finance, Accounting, and GTM. You will help define technical direction, raise the engineering bar, and turn monetization opportunities into trusted, scalable data products and platform capabilities. In this role, you will Design, build, and operate large streaming and batch data pipelines that process product, financial, and operational data from a variety of internal and external systems. Develop canonical data models and reusable data products for domains such as product usage, pricing, billing, ads, payments, revenue, and the general ledger. Establish strong guarantees for data accuracy, completeness, freshness, lineage, reconciliation, and auditability. Build frameworks and platform capabilities that improve developer productivity and make it easier for teams to launch, measure, and iterate on m

About the Team The Plugin Developer Platform team builds the APIs, SDKs, and tools that let people extend ChatGPT and Codex. We work on plugins, connectors, the Model Context Protocol (MCP), and interactive apps. We want anyone to be able to turn a useful workflow into a plugin, share it, and have other people use it. A plugin can package instructions and skills with connections to the tools and data it needs. Our work covers plugin creation and publishing, the systems that run plugins across our products, and open standards that developers can build on. About the Role We’re looking for platform-minded engineers who know what it takes to build a platform developers want to use. You’ll work across developer-facing interfaces, APIs, and backend systems. You’ll own features from the first developer conversation through implementation and release. You’ll talk directly with developers, partners, and the open-source community. Their experience will inform the APIs and abstractions you design, the problems you prioritize, and the tradeoffs you make. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. What You’ll Do Design and ship APIs, SDKs, and services that developers use to extend ChatGPT and Codex. Make plugins easier to create, test, publish, update, and share. Improve compatibility and consistency across ChatGPT and Codex, including interactive app experiences. Contribute to MCP and other open standards, bringing practical developer needs into their design. Work with developers and partners to understand recurring problems and improve the platform, tooling, and documentation. Work with Product, Research, Security, and Trust & Safety on permissions, compatibility, and safe, reliable execution. You Might Thrive Here If You Have built software that other developers use. Your experience might include an open-source project, an API or SDK, a developer platform, internal too

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About Replit Replit is building the world’s most ubiquitous AI coding agent. Replit Agent can be used by anybody to bring their ideas to life. Whether it’s an app for yourself, the next great startup idea, or a tool to make you more productive at work, Replit Agent can help build it. Replit is also the leader in secure vibe coding. We protect apps, give users features to manage security risks, and help them vibe code more safely. About the Role In this role you will build powerful tools that help product engineers iterate rapidly on the Agent experience and directly enhance the core Agent itself. You’ll bridge the gap between the AI team (working on the core Agent logic) and the UX team (crafting delightful Agent experiences), enabling both groups to excel within their specialties. This role blends systems engineering, developer experience and product engineering. We tackle complex challenges across the full stack, from browser-based interfaces to high-performance backends to Linux systems engineering. We’re looking for engineers who have a keen sense of the product experience and how to power it with performant systems. On this team, you’ll have the opportunity to grow your skills across our infrastructure and product, and to lead end-to-end efforts with meaningful impact. We value diverse perspectives and encourage candidates from all backgrounds and experiences to apply. You Will Build high-throughput backend applications and services, like streaming chat between user and agent. Design a collaborative "Multiplayer Computer" that lets humans and AI agents work together on shared shells, filesystems, and state—conflict-free and in real time. Develop infrastructure (frontend & backend) that empowers product enginee

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Team Product Platform builds and owns the shared foundations the rest of Replit is built on, spanning the full stack so every other team can ship features safely and quickly: backend infrastructure, connectors, product primitives, and the frontend platform. Our work is high-leverage and horizontal: when our foundations are solid every other team moves faster, and the role gives you exposure across the whole of engineering. We are a small, collaborative team that values curiosity and clear thinking over pedigree, and we work in the open by bringing each other the problem rather than just the request. We care more about how you reason and build than the route you took to get here. About The Role As a Product Engineer , you can focus on frontend, backend, or full-stack work building the shared systems other teams depend on. The work is guided by a few simple questions: Are our shared systems fast, reliable, and cost-efficient as traffic grows? Are we making product development safe by default, consistent, and faster? Can a builder connect a third-party service once and have it work safely across every app they build? Are user-facing surfaces consistent and fast, with shared primitives teams can build on? Is our codebase easy to navigate, change, and extend, including for AI coding agents? What you’ll do Design reusable primitives and interfaces with clear contracts and documentation that other teams adopt Work directly with product teams to turn their friction into platform improvements Profile and instrument shared systems, then ship the improvements that move latency, cost, and reliability Harden systems against failure and abuse, and make safe defaults the path of least resistance Set technical direction in a

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. Replit is a software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit helps more people build and ship software. About the Team Product Platform builds and owns the shared foundations the rest of Replit is built on: backend infrastructure, connectors, product primitives, and the frontend platform. When these foundations are solid, every other team moves faster. This role goes deep on the frontend platform: the architecture and platform layer behind every core product surface. The work is high-leverage and horizontal, and gives you exposure across the whole of engineering. We are a small, collaborative team that values curiosity and clear thinking over pedigree, and we care more about how you reason and build than the route you took to get here. If you like making other engineers faster, you will fit in here. About The Role As a Product Engineer focusing on the frontend platform , you will own the frontend architecture behind core product experiences: application frameworks, the API and data layer, testing infrastructure, and client performance. The goal is simple: product teams ship quickly and reliably on what you build. The team’s work is guided by a few simple questions: Is our core frontend architecture (frameworks, state, routing, SSR/CSR) sound, consistent, and easy to build on? Is our API and data layer reliable and ergonomic, with clear contracts, sensible error handling, and effective caching? Are user-facing surfaces fast and well-instrumented, with testing infrastructure that keeps them safe to change? Is the codebase easy to navigate, change, and extend, including for AI coding agents? You’ll partner closely with engineering, produc

As Datadog’s in-house product experts, the Technical Escalation Engineering (TEE) team plays a critical role in driving our global success. We enable our customers, from the world’s most innovative startups to the largest enterprises. Through deep technical expertise, relentless problem-solving, and exceptional customer engagement, we educate, guide, and troubleshoot, delivering high-impact solutions that shape the customer experience. Whether through hands-on technical call, in-depth fact findings meeting, or complex investigations, we set the gold standard for technical excellence and customer advocacy. As part of our TEE team, you’ll tackle the most challenging technical problems, collaborate directly with Engineering and Product to refine and evolve our platform, and mentor teams worldwide, elevating the technical bar at every level. As part of the Technical Escalation Engineering (TEE) team, you’ll operate at the heart of Datadog’s ecosystem, working at the intersection of Technical Solutions, Engineering, Product, and our Customers. Every challenge you take on will directly impact the performance, scalability, and success of both our clients and our platform. You’ll be in an environment that moves fast, challenges you daily, and rewards curiosity, ownership, and technical excellence. This is your chance to shape the future of observability and security, driving innovation, mentoring teams, and influencing product direction while witnessing your expertise make an immediate and lasting impact. 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: Develop deep technical expertise and continuously learn as the product evolves. Investigate complex escalations, lead high-stakes technical calls, and drive solutions for our most critical customer cha

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. Who We Are: Every day, tens of millions of people from around the world come to Roblox to play, learn, work, and socialize in immersive digital experiences created by the community. Our vision is to build a platform that enables shared experiences among billions of users. This is what’s known as the metaverse: a persistent space where anyone can do just about anything they can imagine, from anywhere in the world and on any device. Join us and you’ll usher in a new category of human interaction while solving exceptional challenges that you won’t find anywhere else. What You’ll Do: Robux is Roblox’s Virtual Currency: it’s how Users buy virtual items and how Creators earn a living. The Economy Platform team is the owner for all systems powering Robux transactions and has the goal of maintaining Roblox’s Economy healthy and vibrant. As a Principal Software Engineer for Virtual Economy Platform, you will be responsible for improving and scaling Roblox core monetization systems. You will report to Virtual Economy’s Senior Engineering Manager. The scope of Economy’s team includes the several Purchasing, Pricing and Payout systems. Those systems enable developers to monetize their game

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. ML Platform @ Roblox today supports hundreds of ML use cases and billions of inferences per day across Discovery, Safety, Engine, and much more. As an Infrastructure Engineer on the ML Platform team, you will design, scale, and maintain the foundational infrastructure powering our entire machine learning ecosystem. We are looking for accomplished engineers to spearhead the development of our next-generation ML tooling and platform capabilities. You will: Bootstrap and maintain Kubernetes and Cloud infrastructure for ML Platform components--Serving Layer, Metadata Store, Model Registry, and Pipeline Orchestrator. Set technical strategy and oversee development of high scale and reliable infrastructure systems. Propose and implement new platform tooling to improve time to production for MLEs and Data Scientists across the full ML lifecycle. Work on infrastructure projects such as GPU fleet management, hybrid-cloud orchestration, and writing custom Kubernetes controllers and resources. Stay abreast of industry trends in machine learning and infrastructure to ensure the adoption of leading-edge technologies and practices. Partner across organizations to build tooling, interfaces, and visualizati

About the Team Business Systems / Enterprise Platform Technology builds the internal systems, data foundations, workflow infrastructure, and enterprise platforms that help OpenAI operate at scale. The EPT AI Pod builds AI-native internal apps, MCP connectors, multi-agent workflows, and reusable platform capabilities across Finance, People, and GTM. About the Role As an Enterprise Applied AI Engineer, you will build internal apps for enterprise operations and the shared platform components those apps run on. This includes MCP connectors, multi-agent orchestration, data architecture, evals, monitoring, auditability, and governance. We’re looking for a hands-on engineer who is strong in Python, system design, enterprise integrations, data architecture, and applied AI systems. You should be excited to turn ambiguous business workflows into reliable internal products and shared infrastructure. In this role, you will: • Build internal apps for enterprise operations across Finance, People, and GTM • Build MCP connectors and enterprise integrations with strong auth, permissions, idempotency, retries, and rate-limit handling • Design end-to-end multi-agent workflows with tool routing, human approvals, audit trails, and safe action boundaries • Design data architecture for operational AI systems, including ingestion, schemas, quality checks, lineage, and governance • Build evals, monitoring, metrics, and regression tests for agentic workflows • Create reusable infrastructure, patterns, and components that other enterprise teams can build on • Partner with system owners and business owners to turn messy enterprise workflows into reliable internal products You might thrive in this role if you: • Have strong Python engineering skills for backend services, MCP connectors, agent/tool workflows, eval harnesses, and data ingestion jobs • Have strong system design skills across shared infrastructure, app architecture, reliability, and scaling • Have experience building internal apps,

About the Team OpenAI’s Platform team powers how millions of developers and enterprises build with our models. We provide APIs and agentic solutions used by global startups and fortune 500s. We work closely with product, engineering, design, and go-to-market to build a world-class platform that pushes the frontier of AI capabilities. About the Role As a Data Scientist on the Platform team, you will drive a data-driven culture for OpenAI’s API and B2B solutions. You’ll define the metrics that matter for developer success and enterprise value, measure the impact of new models and features, and partner with PMs and engineers to improve model quality, reliability, latency, and cost. Your work will shape how thousands of products adopt agentic AI. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will Embed with the Platform product team as a trusted partner, uncovering ways to improve developer experience, reliability, and usage growth Define north-star metrics across the developer funnel (activation, retention, growth), as well as latency/cost guardrails for new features and models Design and interpret A/B tests and controlled rollouts (e.g., new model versions, pricing/limits, new API features, new B2B products) Build source-of-truth dashboards and self-serve data tools for product, engineering, and go-to-market teams Translate product learnings into actionable feedback for Research (e.g., failure modes, eval gaps, model response quality) You might thrive in this role if you have 5+ years in a quantitative role in ambiguous, high-growth environments (platforms, APIs, or B2B products a plus) Depth in SQL and Python, with a track record proposing, designing, and running rigorous experiments Experience defining and operationalizing metrics from scratch (including reliability/latency/cost and safety) Strong cross-functional communication with PMs, enginee

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Senior Software Engineer — Cortex Training The Snowflake ML Platform team's mission is to let customers run their most demanding ML/AI workloads inside Snowflake. Cortex Training is our LLM post-training platform: it turns scarce, expensive GPU capacity into a simple, composable service, so customers can adapt open-weight foundation models to their own business problems while we handle the hard distributed-systems parts, including scheduling, orchestration, multi-node training and inference, fault tolerance, and throughput. The platform already runs post-training at scale. Under the hood, it decouples GPU computation from the training loop and exposes it as primitive APIs that compose into everything from SFT to full RL workflows. You'll work alongside a team that ships fast & sweats reliability and the researchers behind DeepSpeed. We're looking for an engineer who thrives in the ML infrastructure layer and brings a solid understanding of LLMs and post-training to help us scale and grow it. YOU WILL: Design and build across the full stack — from the public training APIs and SDK through the control plane to the GPU data plane. Scale the distributed systems that make GPU compute serverless — multi-tenant scheduling, placement, and capacity-aware routing across regional G