Jobs in United States

Platform Manager in United States

3,618 active opportunities · Updated October 2026

Explore current platform manager jobs across United States. Filter by work mode, employment type, experience, department, date posted and distance.

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📍 New York, New York, United States· Full-time
✓ High-confidence listingCompany trend -89.8%

From $192K/yr

Quick readStrong listing-quality and freshness signals

Senior Software Engineer - Streaming Platform Client Data streams are mission-critical at Datadog, powering near real-time communication across the vast majority of our services. Our Streaming Platform group builds the core infrastructure and abstractions that ensure Datadog remains a trusted partner for engineers worldwide. See our blog post . The Streaming Platform Client team sits at the heart of this ecosystem. We own the Rust client library (producers and consumers) with language bindings for Java, Go, and Python. We focus on building intuitive APIs and abstractions that make a powerful distributed system easy to adopt and operate for the hundreds of internal users of our library. Our library runs on critical data paths that handle hundreds of millions of messages per second making performance, observability, and reliability paramount. We also develop and operate the service that bridges the clients fleet with the platform's control plane, handling complex balancing, scaling, and static stability challenges. We are seeking a Senior Software Engineer to help us evolve these features. You will collaborate directly with our users, tackle performance-critical code, and solve complex distributed systems challenges across the control plane, client libraries, and data plane. 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 within a distributed, high-impact team spanning Europe and the US, building critical technologies that power data pipelines for dozens of internal teams and hundreds of services. Architect and implement resilient interactions between our client libraries and the control plane. Optimize our high-throughput, low-level streaming library to push the boundaries of performance and efficiency. Champion the developer experience by pro

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📍 Us Cananda, United States· Full-time
✓ Quality checkedCompany trend -95.9%

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Web Presence & Platform (WPP) is organized into two pillars—Platform and Presence. The Platform pillar builds internal systems, tooling, and infrastructure to support the web. The Presence pillar owns the public-facing storytelling across stripe.com and link.com—including our homepage, product landing pages, industry and solutions pages, and other high-impact go-to-market surfaces. Together, we shape how millions of people understand what Stripe is and what it can do for them. Designers on the Presence team work at the intersection of craft and impact—balancing clarity, polish, and systems thinking with strategic storytelling and experimentation. We collaborate closely with engineering, marketing, content, and product to deliver work that is not only beautiful, but measurably moves the business. What you'll do As a Designer on the Presence team, you'll own design across two distinct and high-visibility surface areas—Link (the Stripe one-click checkout experience and link.com) and Bridge (bridge.xyz—the Stripe stablecoin financial infrastructure, operating as its own standalone web property). These are some of the most strategically varied and creatively demanding surfaces in our portfolio—each with its own audience, brand voice, and design challenge. You'll operate with a high degree of autonomy—driving work from brief to launch, navigating ambiguity with confidence, and setting the quality bar for your focus areas. You'll shape the desi

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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -86.4%

About the Team The Platform Systems team at OpenAI operates at the intersection of cutting-edge AI and large-scale distributed systems. We build the engineering and research infrastructure required to train OpenAI’s flagship models on some of the world’s largest, custom-built supercomputers. Our team develops core model training software and works deep in the stack - spanning collective communication, compute efficiency, parallelism strategies, fault tolerance, failure detection, and observability. The systems we build are foundational to OpenAI’s research velocity, enabling reliable, efficient training at frontier scale. We collaborate closely with researchers across the organization, continuously incorporating learnings from across OpenAI into the evolution of our training platform. About the Role As a Software Engineer, Platform Systems, you will design and build distributed systems that provide visibility into large-scale training workloads and help operate them reliably at scale. You’ll work on failure detection, tracing, and observability systems that identify slow or faulty nodes, surface performance bottlenecks, and help engineers understand and optimize massive distributed training jobs. This infrastructure is critical to operating OpenAI’s training stack and is actively evolving to support new use cases and increasingly complex workloads. This role sits at the core of our training infrastructure, blending systems engineering, performance analysis, and large-scale debugging. In This Role, You Will Design and build distributed failure detection, tracing, and profiling systems for large-scale AI training jobs Develop tooling to identify slow, faulty, or misbehaving nodes and provide actionable visibility into system behavior Improve observability, reliability, and performance across OpenAI’s training platform Debug and resolve issues in complex, high-throughput distributed systems Collaborate with systems, infrastructure, and research teams to evolve platform

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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -86.4%

About the Team The Platform Analytics team builds the systems OpenAI researchers use to understand the quality and behavior of the models we train including what models are doing, why they behave in a particular way, and how that behavior changes across experiments. Neptune is a core part of this work. It ingests, stores, queries, and visualizes large volumes of metrics from pretraining, post-training, and reinforcement learning. Hundreds of researchers depend on these systems in their daily work to compare experiments, debug unexpected behavior, and decide what to try next. Our scope is broader than metrics. We also build platforms that help researchers analyze samples, traces, evaluation results, and other structured or unstructured data through dashboards, APIs, and increasingly agent-driven workflows. These systems need to remain fast, reliable, and understandable as the scale and complexity of research change quickly. We are not trying to become a consulting team that builds a separate solution for every research project. We work directly with researchers to understand recurring problems, then turn them into reusable infrastructure and platform capabilities that many teams can build on. About the Role We’re looking for a hands-on experienced software engineer who can take ownership of a critical system and drive it from problem definition through production adoption. This person should be able to own a platform such as CacheHouse end to end: define its technical direction, design its data model and storage architecture, integrate it with several research dashboards and workflows, guide one or two engineers, and ensure the system works reliably for its users. The right candidate should already bring the technical judgment, ownership, and execution expected at this level. The primary learning curve should be OpenAI’s stack and research problem space, not learning how to lead a complex engineering effort or deliver a production system. You will work directly with

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📍 San Francisco, California, United States· Full-time
✓ High-confidence listingCompany trend -100%
Quick readStrong listing-quality and freshness signals

Who Are We? Postman is the world’s leading API platform, used by more than 45 million+ developers and 500,000 organizations, including 98% of the Fortune 500. Postman is helping developers and professionals across the globe build the API-first world by simplifying each step of the API lifecycle and streamlining collaboration—enabling users to create better APIs, faster. The company is headquartered in San Francisco and has offices in Boston, New York, Austin, Tokyo, London, and Bangalore - where Postman was founded. Postman is privately held, with funding from Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. Learn more at postman.com or connect with Postman on X via @getpostman. P.S: We highly recommend reading The "API-First World" graphic novel to understand the bigger picture and our vision at Postman. The Opportunity As the Head of AI Platform Engineering at Postman, you will lead the alignment of AI development with our growing API platform. You will drive the AI roadmap with a focus on expanding AI-driven API collaboration and agentic capabilities across the platform. This role requires a leader who can identify market opportunities, coordinate cross-functional AI initiatives, and foster strong partnerships to amplify the Postman AI platform's impact What You’ll Do Lead the development and execution of Postman’s AI platform strategy, focused on API ecosystem growth and platform innovation. Drive the AI roadmap, concentrating on API integration, platform expansion, and AI-driven agent functionality. Identify and capitalize on market opportunities for AI-enhanced API collaboration and intelligent agent features. Collaborate closely with business units, product teams, engineering, and external partners to ensure alignment and successful AI initiatives deployment. Oversee implementation with core AI platforms (OpenAI, Anthropic, AWS, etc)), ensuring technical and strategic alignment with AI features and API lifecycle improvements.

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📍 Work At Home Texas, United States
✓ Quality checkedCompany trend +340.2%

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 an AI‑native health technology platform that unifies pharmacies, providers, insurers, PBMs, and digital health solutions into a single, consumer‑focused ecosystem. Powered by Google Cloud AI, we’re reimagining personalized and connected health experiences. As a Senior Software Engineer for Health100, you will play a crucial role within a collaborative team — designing, developing, and maintaining backend services and APIs while ensuring releases are well-coordinated, fully prepared, and successfully deployed to production. The ideal candidate brings strong technical expertise in modern backend development, excellent problem-solving skills, and a proactive approach to production monitoring, issue triage, and cross-team coordination. This position is critical in maintaining high engineering standards, ensuring smooth release cycles, and driving operational excellence across the development lifecycle. *This role can be based anywhere in the US; hybrid or remote with preference for candidates to work out of our corporate headquarters in Woonsocket, RI. Responsibilities: Partner with technical leaders and the open-source community to contribute to technical designs, frameworks, roadmap definition, and requirements-gathering. Provide domain knowledge and engineering insight to guide early designs, ac

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📍 Bellevue, Washington, United States· Full-time· Remote
✓ High-confidence listingCompany trend -94.1%
Quick readStrong listing-quality and freshness signals

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

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📍 Massachusetts, New York, United States· Full-time
✓ High-confidence listingCompany trend -89.8%

From $192K/yr

Quick readStrong listing-quality and freshness signals

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

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📍 Mountain View, California, United States· Full-time
✓ Quality checkedCompany trend -86.4%

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

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Relocation support. Relocation assistance is stated. This does not establish visa sponsorship.
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -86.4%

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

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📍 Foster City, California, United States· Full-time
✓ Quality checkedCompany trend -94.8%

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

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📍 Foster City, California, United States· Full-time
✓ Quality checkedCompany trend -94.8%

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

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📍 Colorado, California, United States· Full-time
✓ High-confidence listingCompany trend -89.8%

From $85K/yr

Quick readStrong listing-quality and freshness signals

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

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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -86.4%

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,

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Relocation support. Relocation assistance is stated. This does not establish visa sponsorship.
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -86.4%

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

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