AI Engineering Jobs in San Francisco

Anthropic

The Cybersecurity RL team within Horizons is seeking a Research Engineer to advance the capabilities of AI models in secure coding, vulnerability remediation, and defensive cybersecurity. This role combines research and engineering, involving the design and implementation of RL environments, conducting experiments, delivering work into production training runs, and collaborating with cross-functional teams. The ideal candidate will possess domain expertise in cybersecurity and an interest in training safe AI models, potentially coming from backgrounds such as white hat hacking, security engineering, or detection and response.

$500k - $850k

Glean is seeking a Tech Lead for its Admin Console team to engineer a critical product surface that enables customers to deploy, govern, and scale Glean across their organizations. This high-impact, full-stack role involves guiding architecture, collaborating with product and design, and growing a strategically important team. The Admin Console serves as the control plane for enterprise activation, admin confidence, and scalable rollout, allowing admins to configure authentication, data sources, permissions, governance, search settings, AI features, and deployment health from a central hub. As Glean transitions into an AI platform, this team's focus is expanding from data source management to overseeing the broader system context, including actions, live data, governance, and AI configuration.

$200k - $300k

Anthropic

Anthropic's mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society. The Interpretability team focuses on mechanistic interpretability, aiming to discover how neural network parameters map to meaningful algorithms. This involves reverse-engineering how trained models work, treating neural networks like biological systems or computer programs to be reverse-engineered. The team's goal is to create a solid scientific foundation for understanding neural networks and making them safe, with a focus on issues like "superposition" and decomposing models into interpretable components. This role supports a team of expert researchers and engineers working on these ambitious safety research goals.

$350k - $500k

Glean is building a world-class Data Organization composed of product data science, applied science, data engineering, and business intelligence groups. This is an applied science role based in our San Francisco office. You will collaborate with product data science and engineering teams to identify techniques, tooling, and process improvements in online A/B experimentation to assist rigorous decision-making across all relevant product domains. You will develop and maintain our A/B experimentation platform based on stakeholder feedback, and write code or identify vendors to deploy these techniques to production in a scalable manner that’s easy to use by engineering, product data science, product management, and design teams. You will also conduct end-to-end evaluation of various hero use cases like document/URL uploads, including evaluation set generation, coming up with evaluation criteria and methods to interpret the results. You will break down end-to-end evaluations into more granular evaluation of various tasks & skills including but not limited to content summarization/analysis/generation, multi-step reasoning & strategizing, tool selection & use, coding & system design. You will design, develop, and own best practices, tools, and processes across various evaluation problems, e.g., query intent classification, standardizing the use of best statistical principles to handle LLM stochasticity, and industry benchmarking.

$180k - $330k

Anthropic

The Interpretability team at Anthropic is dedicated to understanding how modern language models work, believing that a deep, mechanistic understanding is crucial for making advanced AI systems safe and steerable. This role involves building and maintaining the specialized infrastructure that powers interpretability research, akin to performing 'neuroscience' on neural networks. The work spans the entire lifecycle of a production language model, from pretraining and inference to performance optimization, and directly contributes to safety audits on frontier models.

$315k - $560k

Glean is seeking a founding Forward Deployed Engineer to join their team and operate with the autonomy and accountability of a founder. This role involves discovering and building Glean's next generation of product surfaces, working in a pod with Forward Deployed PMs directly with the C-suite of influential companies and Glean's engineering and product teams. You will identify the biggest unsolved business problems at strategic customers, build entirely new products to solve them, and in doing so shape the future of Glean. The best of what you build will ship to every Glean customer globally, offering founder-level ownership with Glean's resources and scale.

$160k - $270k

Anthropic

The Interpretability team at Anthropic is dedicated to reverse-engineering how trained models work, believing that a mechanistic understanding is crucial for making advanced AI systems safe and steerable. This role focuses on mechanistic interpretability, aiming to discover how neural network parameters map to meaningful algorithms, akin to performing "biology" or "neuroscience" on neural networks. The team has made significant progress in understanding issues like "superposition" and decomposing models into interpretable components, with recent work identifying millions of features in production models and developing methods to understand multi-hop reasoning and planning. This research is foundational for building reliable, interpretable, and steerable AI systems and often involves collaboration with other teams at Anthropic to enhance AI safety.

$350k - $850k

Glean is seeking a Backend/Infrastructure Engineer to build and evolve the Storage layer that powers a highly available, performant, secure, and cost-effective suite of storage options for all data at Glean. You will own the storage systems that handle Glean’s most sensitive data, from enterprise documents and permission hierarchies to user behavioral signals and real-time query path data. Your work will directly enable organizations at scale to discover and act on their critical knowledge, supporting millions of searches, chat interactions, and agent workflows. You’ll deliver robust uptime guarantees, autoscaling, and reliable alerting/monitoring for a key component that runs across multiple cloud providers. As part of the Storage team, you’ll be responsible for a critical piece of Glean’s infrastructure, working closely with several other teams to support their workloads. You’ll also work across the stack to abstract cloud differences, reduce human intervention through self-healing systems, and drive real business impact by enabling Glean’s ever-growing scale.

$200k - $300k

Glean is seeking creative engineers to own and launch delightful user-facing features for its Work AI platform. This role involves developing ideas with product managers and designers, balancing engineering constraints with requirements to deliver intuitive experiences for modern mobile and desktop browsers. You will oversee greenfield features from inception to launch, architecting robust REST APIs and writing efficient, maintainable code. This is an opportunity to shape how the world works by building systems used daily across major platforms and embedding agentic capabilities into an open, extensible stack.

$140k - $265k

Glean is seeking a Software Engineer, Developer Productivity to enhance how our engineers build, test, and ship software. This role involves optimizing our multi-language codebase, which is powered by Bazel and runs on GitHub Actions with cloud remote execution. You will be instrumental in designing and refining build systems, CI/CD pipelines, and developer tools. A key aspect of this position will be enabling engineers to effectively utilize AI-powered coding and productivity tools, ultimately reducing friction in daily workflows, scaling our infrastructure, and accelerating the entire engineering team's progress with confidence.

$140k - $220k

Glean is building the horizontal AI platform that powers how employees use AI at work, extending beyond Glean to tools like Copilot, Gemini, and ChatGPT. This team is responsible for the end-to-end platform experience, including standards and tooling for REST APIs, SDKs, client libraries, agent SDKs and integrations, MCP servers, custom context like code and memory, and the supporting infrastructure and documentation. As part of a rapidly growing startup, this role involves working across multiple layers of the stack, from backend services to developer tools and SDKs.

$210k - $300k

Glean is seeking driven engineers to tackle cutting-edge challenges in data and AI security and governance. In this fast-paced startup environment, you will empathize with customer needs, research the domain, and devise novel solutions to complex problems. You will collaborate with product managers and designers to balance engineering constraints with requirements, delivering intuitive and reliable experiences for enterprises to ensure user safety.

$140k - $265k

Glean is seeking software engineers to contribute to building a leading search and assistant product for the workplace. Engineers will work across the technology stack, focusing on areas such as generative AI, Retrieval Augmented Generation (RAG), query and document understanding, domain-adapted language models, natural language question-answering, and evaluation. The role involves close interaction with customers to understand their challenges and applying the most effective tools to solve them.

$175k - $270k

Thinking Machines Lab

Thinking Machines is building AI that extends human will and judgment. We are developing Tinker, a fine-tuning API that empowers researchers and developers to customize frontier AI models. This role focuses on building and enhancing our training systems for Tinker, specifically involving RL systems, numerics, and kernels, to enable users to train models with their own data and algorithms.

$350k - $475k

OpenAI

The Agent Post-Training team at OpenAI is responsible for developing the frontier agents that are shipped to users. This involves training models for products like Codex and ChatGPT, focusing on creating persistent, proactive intelligence that can operate computers, collaborate with humans and other agents, and expand user capabilities. The team defines the next generation of agent abilities, builds the training signals, and runs experiments to realize these advancements. The role specifically focuses on teaching models to operate computers, including navigating browsers and desktops, using tools, reasoning through complex workflows, and completing long-horizon tasks reliably. This position is at the intersection of frontier model training, product behavior, evaluation, and systems engineering, directly influencing the computer-use capabilities of OpenAI's future agents.

$380k - $500k

Anthropic

Anthropic's customer-facing teams are often the first place a customer sees what Claude can do. As a Demo Engineer, you'll build the demos, reference implementations, and reusable tooling that help those teams make new capabilities tangible, relevant, and trustworthy, ideally within days of a product launch rather than weeks after. This role sits between product engineering, technical storytelling, and GTM execution. You'll own ambiguous, high-leverage problems end to end: prototyping an agentic experience for a new capability, then hardening it into something reliable that other teams can run on their own. You'll work closely with Product, Engineering, Marketing, Operations, and our sales and solutions teams, and you'll bring what you learn from customer-facing work back to the people building the products. Because a demo is frequently someone's first impression of what our models can and can't do, accuracy and honesty matter as much as polish. Success in this role looks like customer-facing teams demonstrating new capabilities sooner and with more confidence, recurring requests becoming reusable assets rather than one-off projects, and field insights shaping product and launch-readiness decisions.

$240k - $315k

As a Developer Platform engineer at Notion, you will contribute to the foundational elements that make Notion extensible and connected. You will build tools, APIs, and platform experiences enabling customers to integrate Notion with their external applications, data, and workflows. Your work will empower developers, admins, and builders to create reliable integrations and automations, making it easier to bring their apps and data into the Notion workspace. You will be a key player in establishing the robust technical foundation for Notion's connected workspace vision, contributing to both internal platform improvements and end-user-facing functionality. This role involves tackling complex technical challenges to ensure the long-term quality, reliability, and performance of Notion's platform as it scales.

$179k - $200k

Genmo is a research lab developing sophisticated video world models to understand, simulate, and interact with the physical world, aiming to unlock the right brain of AGI. We are seeking an exceptional Research Scientist to focus on alignment and post-training techniques for large-scale video generation models. This role is at the forefront of ensuring our diffusion-based video models reliably produce high-quality, physically accurate, and safe outputs that align with human preferences and values.

Salary not listed

Amplitude

Amplitude is seeking a Staff Software Engineer to join their Query team, focusing on their in-house OLAP engine, Nova. This role is critical for powering AI agents that will autonomously ship features, run experiments, and make prioritization calls. You will work across the full stack of a modern OLAP system, including query planning and execution, columnar storage, distributed compute, caching, and cloud infrastructure. The goal is to drive significant improvements in performance, cost-efficiency, and reliability at scale, ensuring Nova can handle the increasing demand from non-stop AI agents. This position offers the opportunity to influence technical direction, mentor other engineers, and make a tangible impact on a system that serves thousands of customers.

$198k - $299k

Browserbase

Browserbase is seeking a Software Engineer to join the Agent Platform team. This team operates at the intersection of AI and open source, building developer tools that make browser automation smarter, simpler, and more powerful. You will be responsible for building, operating, and growing the Agent Platform framework, which includes developer-first APIs with significant monthly downloads and stars. The role involves designing and implementing tools for web automation, collaborating with leading AI labs to improve models and make them accessible, and deploying production-ready AI solutions that impact millions of users. You will also help define and prioritize projects that shape the future of developer tooling and contribute to documentation and knowledge sharing.

$180k - $300k

Ironclad is seeking a Technical Lead Manager to lead a team of engineers focused on building production generative AI systems. This role combines hands-on technical leadership with people management, involving setting the technical direction for the team and fostering engineer growth. The team will own the technical roadmap and quality bar for their systems, partnering with product management to translate business needs into technical deliverables. The Tech Lead Manager will also contribute directly through design documents, architectural decisions, and writing production code for critical problems. A key aspect of the role is staying deeply involved in the team's architecture and technical details to effectively review designs, unblock engineers, and make prioritization calls, while also setting and upholding high engineering standards for code quality, testing, and production monitoring.

$188k - $235k

Together AI

We are seeking a software engineer to develop a Kubernetes-native control plane for provisioning and managing our GPU inference fleet. This role involves designing a manifest-driven API that allows the inference team to declare their needs, such as clusters, model deployments, or capacity adjustments. Our controllers will handle the underlying reconciliation, provider/runtime selection, and lifecycle management, abstracting away the complexities of the serving stack, scheduler, or hardware pool. You will also build systems to ensure fleet efficiency, including defragmentation, rebalancing logic for consolidating workloads, and scheduling/bin-packing improvements to maximize GPU utilization without compromising latency. The core objective is to decouple platform users from operational complexities while optimizing hardware capacity. This includes developing controllers, reconciliation loops, and self-service interfaces (API/CLI) for seamless operation, alongside event-driven systems for health monitoring, remediation, and utilization management, all designed to operate without human intervention. A product-oriented mindset is crucial, with a focus on building internal platforms and APIs that enhance the developer experience for consuming engineering teams. This role operates under a "you build it, you own it" philosophy, encompassing both software delivery and production support.

$160k - $280k

Prime Intellect

Prime Intellect is building the open superintelligence stack, providing infrastructure for AI labs. Their platform, Lab, unifies compute, environments, evaluations, and training/deployment for post-training at scale, including SFT, RL, and agent workflows. They are developing open-source models for long-horizon tasks and the platform their research team uses. The company has raised significant funding and is looking for individuals passionate about frontier research, infrastructure, and go-to-market strategies in a nascent category.

$150k - $350k

Typeface

We help the world’s biggest brands move from brief to fully personalized campaigns — in days, not months. Founded by Abhay Parasnis and backed by Microsoft, GV, Salesforce, Lightspeed, Madrona and Menlo, we’re building category-defining technology at the intersection of creativity and AI with real impact. Join us to help shape the future of enterprise marketing. We're looking for a Staff Infrastructure Engineer to help lead core parts of our platform. You'll design, build, and scale the cloud infrastructure that powers our AI and GenAI workloads — ensuring reliability, security, and performance as we grow. This is your chance to shape the backbone of a platform trusted by Fortune 100 companies — building systems that are resilient, observable, and ready to scale with the next wave of AI.

$210k - $240k