Full Stack Builder Manager Specialist in San Francisco

Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. At Amplitude, we’re building the operating system for digital products. While we’re known as the leader in product analytics, our Statsig team is redefining how companies learn, iterate, and ship better experiences. Statsig is one of the fastest-growing and most strategic bets at Amplitude. It sits at the intersection of product, data, and decision-making, and we’re looking for a Product Engineer to help take it to the next level. Why this role matters This isn’t a “take tickets and ship code” role. You’ll operate as an owner, shaping both the product and the technical direction of a system used by some of the most sophisticated product teams in the world. You’ll work across the stack, NextJS and Node.js, to build intuitive, high-performance experiences that make experimentation accessible, powerful, and trustworthy. What you’ll do Own critical product surf

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform providing APIs for knowledge retrieval, inference, evaluation, and more. We are seeking a strong Senior Full-Stack Engineer to help us build, scale, and refine our rapidly growing product. The ideal candidate is deeply grounded in software engineering best practices and experienced in developing and scaling modern web applications end-to-end. You will work across the stack—from React/TypeScript frontends to Python-based backends—while integrating with LLMs and machine learning systems. You will solve complex challenges in scalability, reliability, and product experience while owning significant product areas in a fast-paced environment. What You’ll Do Own major full-stack product areas , driving features from design through production deployment. Build modern frontend experiences using React and TypeScript, ensuring performance, usability, and responsiveness. Develop reliable backend services in Python, working with distributed systems, data pipelines, and ML/LLM components. Integrate with LLMs, vector databases, and AI infrastructure to power intelligent product experiences. Deliver experiments and new features quickly , maintaining high quality and tight feedback loops with customers. Collaborate across product, ML, and infrastructure teams to shape the direction of Scale GP. Adapt quickly —learning new technologies, frameworks, and tools as needed across the stack. Ideal Experience 5+ years of full-time engineering experience , post-graduation. Strong experience developing full-stack applications using React, TypeScript, and Python . Experience scaling or shipping products at high-growth startups . Familiarity with LLMs, vector databases, embeddings, or other modern AI tooling (tinkering or production experience welcome). Proficiency with SQL and modern API development. Experience with Kubernetes , containerization, and microservice architectures. Experience working with at leas

About the Team Come help us build and develop tools serving hundreds of engineers internally! We’re looking for a Fullstack Software Engineer to join our Developer Insights team. About the Role Our mission is to improve the developer experience of engineers at DoorDash by building various internal products, including our internal developer portal, Developer Insights. Our success as a platform team depends on the success of the product teams we serve. Because of this, we invest in building a strong community that encourages participation and promotes best practices. You’re excited about this opportunity because you will… Introduce cutting edge technologies to our engineering organization, including tools built on LLMs Build new features for Developer Insights (using Backstage.io) Improve the developer experience for all of our engineers Work and collaborate across team boundaries. Contribute features and bug fixes to upstream open-source projects. Mentor and educate your peers. Lead the team in a technical fashion and assist in roadmap planning and measurement of existing features. Represent the team at large in OKR and engineering all-hands presentations. Context switch from frontend to backend to data depending on the need that arises. We’re excited about you because… You have at least 2 years of experience in web technologies using Typescript with React on the frontend with Java, Kotlin, Python or Go backend experience. You have a product mindset and apply that to how you would build out platform services. You love systems and software, and you're proficient in both. You’re curious and dive deep into different system architectures. You are an organized and excellent written and verbal communicator. You have proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software Compensation The successful candidate’s starti

About Scale Scale’s mission is to develop reliable AI systems for the world’s most important decisions. As the leading AI data foundry, we provide the high-quality data and full-stack technologies that power the world’s most advanced models — fueling breakthroughs in generative AI, defense, and autonomous vehicles. We partner with leading enterprises and governments to bring AI into production that performs when it matters most, combining rigorous evaluation with full-stack deployment so our customers can build AI they can trust. About the Team Applied Intelligence Systems (AIS) is part of the Scale Generative AI Platform (SGP), focused on pushing the frontier of what agentic applications can do across diverse enterprise and government use cases. We build the infrastructure and tooling that power agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale our customers demand. AIS spans multiple workstreams — agent evaluation and oversight, orchestration and tool-use infrastructure, model and systems optimization, and applied research on new agent capabilities — and this role is not scoped to any single one of them. We’re growing fast, with increasing traction across both commercial and public sector customers, and we’re just getting started — this team will define what dependable, production-grade agentic AI looks like. About the Role As a Staff Machine Learning Research Engineer, you will operate across the full breadth of AIS’s technical needs — wherever the hardest ML problem in agentic AI happens to be that quarter. This could mean training and fine-tuning models, designing evaluation and observability systems, building improvement loops from production data, prototyping novel agent architectures, or designing internal systems and tooling that boost productivity across teams. You’re not tied to one team’s roadmap; you’re expected to move to where the technical leverage is highest, and t

About Scale AI At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. Scale Frontier Data is the organization behind the training and evaluation data that frontier labs depend on. We build the systems, tooling, and expert workflows that turn hard human expertise into signals that models can learn from, across reasoning, coding, agentic tool use, and domain expertise. Reinforcement learning environments are now the center of gravity for that work: the difference between a model that demos well and a model that reliably completes long-horizon work is almost always the quality of the environments and reward signals it was trained against. Responsibilities As a Staff Software Engineer, RL Environments, you'll own the technical foundation for how Scale builds, runs, verifies, and delivers RL environments at scale. An RL environment is a real piece of software: a containerized world with real dependencies, real state, real tools, and a grader that has to be correct even when the agent is creative about breaking it. Building one is a full-stack engineering problem. Building thousands of them reproducibly, cheaply, with trustworthy reward signals and throughput measured in millions of rollouts is a systems problem that very few people have solved. You'll work on both. You'll design the platform: sandboxed execution, environment packaging and versioning, rollout orchestration, trajectory capture, verifier frameworks, and the authoring surfaces that let engineers and domain experts produce environments without reinventing infrastructure each time. And you'll go deep on the environments themselves by instrumenting real applications, designing task suites that expose specific capability gaps, and building graders that

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. Scale Frontier Data is the organization behind the training and evaluation data that frontier labs depend on. We build the systems, tooling, and expert workflows that turn hard human expertise into signals that models can learn from, across reasoning, coding, agentic tool use, and domain expertise. About our Customer Platform team: Our Customer Platform Team plays a pivotal role in integrating our platform with external systems and ensuring seamless, reliable connectivity for both internal users and customers. As the leader of this team, you’ll drive the strategy, architecture, and development of our connectivity solutions, focusing on API integration, distributed systems, and a robust data platform. Your role will be crucial in maintaining and enhancing our platform’s ability to meet the needs of both our internal and external stakeholders. Responsibilities: Own large areas within our product Comfortable working cross functionally, whether that be internal or external customers Build features end-to-end: front-end, back-end, system design, debugging and testing Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Influence the culture, values, and processes of a growing engineering team Inspire and mentor less experienced engineers Collaborating with cross-functional teams to define, design, and ship new product features and experiences. Requirements: At least 7-10 years of relevant experience is preferred Track record of shipping high-quality products and features at scale Desire to work in a very fast-paced environment Abil

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. For 10 years, Scale has provided the high-quality data and full-stack technologies that power the world's leading models, and has helped enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. Scale's internship is not a side project. Interns own real, shipped work on the same roadmaps as full-time engineers, with mentorship from world-class talent and a culture that values ownership, speed, and truth-seeking. Many of our interns return as full-time Scaliens. Example Projects Build reinforcement learning and post-training data pipelines that power frontier model development Develop evaluation infrastructure that measures model reliability for enterprise and public sector customers Ship agentic AI applications and the tooling that makes them observable, testable, and safe to deploy Ship tools that accelerate the growth of new qualified contributors on Scale's platform Build fraud-detection systems that remove bad actors and keep Scale's contributor base safe and trusted Use models to estimate the quality of tasks and contributors, and guarantee quality on requests at large scale Devise advanced matching algorithms that pair contributors to customers for optimal turnaround and accuracy Create optimized and efficient UI/UX tooling, in combination with ML algorithms, for 100k+ contributors completing billions of complex tasks Develop new AI infrastructure products to visualize, query, and explore Scale data Requirements A graduation date in Fall 2027 or Spring 2028 with a Bachelor's degree (or equivalent) in a relevant field (Computer Science, EECS, Computer Engineering, Statistics) Available for a Summer 2027 internship (May/June start dates) in San Franci

Scale GP is Scale's enterprise Generative AI platform—APIs and infrastructure for knowledge retrieval, inference, evaluation, and intelligent automation. We power mission-critical workflows for leading enterprises, helping teams turn complex data and models into reliable, production-ready AI systems. We're building a new AI Enablement team to create the next generation of agent-powered tools that ground AI in real operational workflows. Our goal: help internal teams demystify their own workflows, then deploy agentic systems that reason over data, take action, and deliver measurable outcomes. We don't build in a vacuum. You'll use our own platform to solve real business problems internally—then selectively commercialize that same stack for customers. What we run on is what we sell. This is a 0→1 team. We're looking for a sharp, product-minded engineer who thrives in ambiguity, moves fast, and loves building systems from scratch alongside customers and cross-functional partners. You'll work closely with product, forward-deployed engineers, data scientists, and applied AI teams to turn real-world problems into scalable production solutions. If you like shipping fast, owning outcomes, and working across the stack—from polished frontends to distributed backends to LLM integrations—this role is for you. What You’ll Do Own full-stack features and projects end-to-end — from design through production deployment — within a larger product area Sample surfaces - Accounting Agents, Finance Copilots, GTM Agents, Agentic Experimentation Platforms Develop reliable backend services in Typescript/Python, work with distributed systems, data pipelines, and AI/ML infrastructure Integrate LLMs, vector databases, and agentic frameworks to power intelligent workflows Ship quickly through tight experimentation loops while maintaining high quality and reliability Adapt across the stack and learn new tools as needed to solve real problems end-to-end Ideal Experience 3+ years of full-tim

Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to transform how work gets done. Airtable’s mission is to bring the power of computing and software development to everyone. We are developing a powerful and extensible toolkit that our customers can leverage to solve a variety of different problems and workflows. We’ve seen our most sophisticated customers use the product to run global processes across thousands of employees, coordinate precision manufacturing pipelines, and consolidate previously siloed mission-critical data into a single source of truth. The complexity of these use cases requires us to be extremely thoughtful about how we design and implement new functionality in the product and make sure it’s both easy to use and comprehend for our customers and maintainable for us. As a Full-Stack, Backend engineer at Airtable, you will have the opportunity to work with customers to deeply understand their needs and workflows. You will collaborate with cross-functional partners across product management, design, research and data science to create innovative new features that enable our customers to do their best work. You will be responsible for owning and executing the end-to-end implementation of these new features that will contribute to making our toolkit even more powerful and successful. We currently have openings on: The Admin & Governance Team (Full-Stack/BE) ensures Airtable is secure, compliant, and enterprise-ready. It owns key admin capabilities like the Admin Panel, SSO, and audit systems, as well as foundational features like User Groups. This team's mission is to accelerate organizational value for the largest customers with enterprise-first governance and controls. The Omni Capability & Quality Team (Full-Stack/BE) brings the power of AI directly to Airtable end users—

Scale AI is seeking a highly skilled and motivated Software Engineer, Frontier AI Infrastructure to join our dynamic Public Sector Engineering team. As a part of this team, you will own the model inference layer - enabling state of the art models, debugging the latest AI tools, managing networking, debugging latency, and tracking pricing/usage metrics for AI models. You will lead technical discussions on the frontlines with cloud vendors and customers to deliver on critical contracts and to debug platform issues. You will also work upstream with Product to understand features before they break, moving us from "infra-only debugging" to proactive integration testing. You will: Design and implement secure scalable backend systems for Public Sector customers, leveraging Scale's modern and cloud-native AI infrastructure. Own services or systems and define their long-term health goals, while also improving the health of surrounding components Re-architect the stack to run in compliant or restrictive environments. This requires designing swappable components (auth, storage, logging) to meet government/security mandates without breaking the product. You will work with Product to build integration tests that catch issues early, shifting the focus from "infra-only debugging" to preventing failures upstream. Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions. Contribute to the platform roadmap and product strategy for Scale AI's Public Sector business, playing a key role in shaping the future direction of our offerings. Must have: At least an active secret clearance and the ability & willingness to up level to TS/SCI with CI Poly. This is a requirement and candidates will not be considered who do not hold at least a secret clearance Ideally you'd have: Full Stack Development: Proficiency in both front-end and back-end development, including experience with modern web develo

About the Team At DoorDash, we’re reimagining how people connect with the things they need — whether it’s a meal, a grocery run, and anything in between. Our audiences — Consumers, Dashers, and Merchants — are at the heart of everything the Design org builds. Our content design team plays a big part in this, with each content designer shaping the experience and bringing our vision to life through clear, thoughtful language that makes our three-sided marketplace easier, faster, and more human. About the Role We’re looking for a full stack UX Design Engineer to be the technical backbone of our global Content Design org and leader who builds the platforms, tooling, and ML systems that make world-class, localized product content effortless across DoorDash, Wolt, and Deliveroo. You’ll work at the intersection of design and engineering to build content tooling and embed LLM-driven workflows into product experiences. You’ll accelerate content design AI tooling so that CD’s can focus on the highest leverage strategic work, while your tools enable product designers and cross functional partners to ship high-quality content faster across DoorDash, Wolt, and Deliveroo. You're excited about this opportunity because... Design and build internal content tools that: Help PMs and designers generate, manage, localize, and deploy product content at scale. Plug custom GPTs and other LLMs into everyday product workflows for content iteration and improvements. Own full-stack development of these tools: Build and maintain frontend experiences using React and modern JavaScript/TypeScript. Design and implement backend services and APIs (e.g., Kotlin/Java) to support content tooling, experimentation, and automation. Integrate tooling with experimentation and infra: Embed content tools into A/B testing platforms so teams can test and ship variants with minimal engineering dependency. Build pipelines from variant generation → experiment → automated deployment of winners. Operationalize

About the Team DoorDash is looking for an Engineering Manager to lead our Discovery Experience team, which owns the Homepage - DoorDash’s front door. It’s the first screen millions of consumers see every day, and since every session starts there, it’s the highest-leverage surface in the consumer funnel: a more personalized recommendation, a faster render, or a cleaner layout can move the metrics the whole company watches. The Homepage spans restaurants, grocery, and emerging verticals across iOS, Android, and Web. We’re rebuilding it around LLM-generated recommendations, shifting discovery from static, rules-based feeds to generative, intent-driven experiences that respond to real-time signals in the moment. About the Role You will lead and grow a team of product-focused full stack engineers, owning both the product and technical direction for the discovery surface - deciding where discovery goes next and how it’s built. You’ll set the roadmap and drive execution alongside Product, Design, Data Science, and ML/Recommendation Platform partners, and you’ll own the quality, velocity, and consumer impact your team ships. It’s a role with real ownership and the room to grow both the product and the team behind it. You’re excited about this opportunity because you will… Own the Homepage end to end, the highest-traffic surface at DoorDash and where every consumer session begins Turn Homepage bets into company-level outcomes: real lift in conversion and order rate for millions of consumers Define discovery quality for DoorDash: getting the right store, restaurant, or item in front of the right consumer at the right moment Ship LLM-gen recommendations and intent-aware discovery that route consumers to the right experience across food, grocery, retail, and emerging verticals Partner across Product, Design, Data Science, and ML/Recommendation Platform teams to shape the discovery roadmap and ship the experiences behind it Build an inclusive, high-performing team by coaching en

Location: San Francisco, CA (Remote/Hybrid Available) What is Verse? The race to AI has become the race to power. Every breakthrough in artificial intelligence depends on one thing: access to electricity. But across the country, aging grid infrastructure and years-long interconnection queues are slowing the deployment of the data centers that will power the next generation of innovation. Solving this challenge isn't just about energy—it's about unlocking the future of AI. At Verse, we're building the energy intelligence platform for the AI economy. Our software helps the world's largest energy consumers achieve faster, cheaper, and cleaner power by combining real-time control of energy assets with complete visibility into their energy portfolio. Backed by Bessemer Venture Partners, GV, Coatue, and NVIDIA, and built by pioneers in grid-scale batteries, energy markets, and enterprise software, we're redefining how the world's most ambitious organizations access and manage energy. The Role You will be a member of the technical staff developing product experiences for our Dispatch Intelligence users – customers who want and have battery energy storage systems for additional energy cost savings or faster interconnection times. In this role, you will serve in a “full stack” capacity designing, building, and maintaining frontend and backend components of our energy storage suite of applications. We use Typescript, React, Next.js, Tailwind CSS, Radix/ShadCN, Jest, Cypress, Playwright, Vitest, and Storybook with Echarts and D3/Observable for data visualization for our frontend, and Cloudflare Pages for hosting and content delivery. We rely on identity and auth platforms like Clerk for sign-in flows. Our backend is written in Go and Python with Postgres/AlloyDB and blob storage for data persistence. Key Responsibilities Foster a culture and mindset of well-designed systems, test-driven software, and proactive communication with a high degree of transparency, mutual resp

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Staff Software Engineer, you will orchestrate the implementation of vertical features and horizontal capabilities to include mentoring other engineers on defining requirements with stakeholders and communication tradeoffs of technical implementations on feature and capabilities until they are accepted by the stakeholders. You will: Orchestrate feature implementation across the Federal engineering team to ensure architectural consistency. Define technical strategy for agentic guardrails, explainability, and fleet orchestration. Ensure system reliability and performance across multiple security classifications and network types. Mentor engineers in the process of defining requirements with stakeholders and gathering acceptance. Communicate high-level technical trade-offs and implementation strategies to senior government stakeholders and Scale C-Suite members. Influence the long-term product strategy and technical roadmap for the Federal business unit. Consult on the architecture of AI-powered solutions for large-scale federal contracts. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in