Вакансии

Own the design, build and optimisation of automated journeys across all four funnel stages. Manage audience, segmentation, entry and suppression logic.

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Location: Remote, Texas, United States, AMER From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven. About Us Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on. Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions. As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact. During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites. About the Role We’re looking to hire a Solutions Engineer, Enterprise to join our Field Engineering team. As a Solutions Architect, you will be a trusted technical advisor to some of our largest and most strategic customers, helping them evaluate, adopt, and expand their use of dbt. You’ll partner closely with Sales to understand customers’ technical and business priorities, design solutions using the dbt platform, and demonstrate measurable value throughout the evaluation process. You’ll work across the customer lifecycle—from technical discovery and evaluation through adoption and expansion—while partnering with Product, Engineering, and our technology partners to bring customer needs back into the business. This is a full-time position based remotely from Texas. Technologies You’ll Use SQL, dbt, cloud data warehouses and lakehouses including Snowflake, Databricks, and BigQuery, AWS, Azure, and GCP, modern data integration and orchestration technologies, and AI-assisted productivity tools. What You’ll Do Lead technical discovery with enterprise customers, connecting technical requirements to business outcomes and measurable success criteria Design enterprise-grade data transformation and analytics architectures using dbt Partner with Sales to communicate the technical and business value of the dbt platform Lead customer evaluations and technical validation, including trials and proof-of-value engagements when appropriate Build trusted relationships with technical practitioners, data leaders, and executive stakeholders Guide customers through technical architecture, security, governance, and deployment considerations Partner across the customer lifecycle to support successful adoption and identify opportunities for expansion Bring customer and field insights to Product and Engineering to help influence product strategy and roadmap Build strong relationships with technology and consulting partners, including Snowflake, Databricks, AWS, and other members of the modern data ecosystem Contribute technical expertise, reusable best practices, and thought leadership to the broader Field Engineering organization and dbt community Skills We’re Looking For 4+ years of experience in sales engineering, solutions architecture, consulting, or a similar customer-facing technical role within data, analytics, or BI Strong technical foundation in SQL, data transformation, ETL/ELT, and data modeling Strong understanding of modern cloud data warehouse, lakehouse, and analytics architectures Ability to uncover and translate technical and business requirements into concrete solutions and measurable outcomes Excellent written and verbal communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences Ability to establish credibility and build trusted relationships with stakeholders ranging from data practitioners to senior executives Ability to operate effectively in a fast-paced, evolving environment while collaborating across Sales, Product, Engineering, and Customer teams Bonus Skills​ Experience with dbt or analytics engineering Experience with Snowflake, Databricks, BigQuery, or other modern cloud data platforms Experience with data modeling methodologies such as dimensional modeling, Kimball, Data Vault, or 3NF Experience with enterprise data integration or ETL platforms such as Informatica, Boomi, or Talend Experience supporting complex enterprise technical evaluations, migrations, or transformation initiatives If you are excited about this role and know that you could get there, but don’t have 100% of the qualifications listed above, please still apply! We value diverse perspectives and want to build the best team we can, and acknowledge that sometimes the right people won’t check every box on a list. The compensation range displayed on this job posting reflects the minimum and maximum target for new hire compensation for the target position and level, and may include sales incentives or target bonuses depending on the role.  Our compensation ranges are determined by role, level, and location. Our job titles may span more than one career level. Within the range, individual compensation is determined by additional factors, including job-related skills, experience, relevant education or training, business need, market demands. The compensation range is subject to change and may be modified in the future. Your recruiter can share more about the specific compensation range for your location during the hiring process. Pay Range $197,512 — $260,607 USD Perks and Benefits 100% employer-paid medical insurance * Generous paid time away from work, including paid vacation or flexible/unlimited vacation depending on role and country, plus paid sick time, inclusive parental leave, paid holidays, including a year-end Global Week of Rest, and volunteer days off. RSU stock grants* Professional development and training opportunities Company virtual happy hours, free food, and fun team-building activities Monthly cell phone stipend Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self-guided mindfulness exercises for all covered employees and their covered dependents. * May vary by country and worker type - please reach out to your recruiter for more information Click here to learn more about Fivetran's Benefits by Region. We’re honored to be valued at over $5.6 billion , but more importantly, we’re proud of our core values of Get Stuck In, Do the Right Thing, and One Team, One Dream . Read about us in Forbes . Fivetran brings together high-quality talent across the globe to make data access as easy and reliable as electricity for our customers. We value and recognize that our customers benefit from having innovative teams made of people from many backgrounds, experiences, and identities. Fivetran promotes diversity, equity, inclusion & belonging through attracting, recruiting, developing, and retaining a diverse workforce, not only because it is the right thing to do, but because it helps us build a world-class company to better serve our customers, our people and our communities. To learn more about Fivetran’s culture and what it’s like to be part of the team, click here and enjoy our video. To learn more about our candidate privacy policy, you can read our statement here . We are committed to ensuring that all candidates have an equal opportunity to participate in our interview process. If you require accommodations at any stage of the process due to a disability, medical condition, or any other circumstance, please don't hesitate to submit your request by filling out this form . We will work with you to provide reasonable accommodations to facilitate your participation and ensure a fair and accessible interview experience. Your request and any information provided will be kept confidential and will not impact your candidacy. We look forward to hearing from you and accommodating your needs to the best of our ability.

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Location: Remote Workplace: Remote ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE As a Solutions Architect at Baseten you will partner closely with Sales and customers to translate business needs into technical solutions, run technical discovery, and guide repeatable deployments and proofs of value for customers. This role is a great fit for entrepreneurial, customer-facing technical professionals who want a front-row view into how modern companies adopt AI at scale, and who enjoy working across technical discovery, solution design, demos, deployment scoping, and hands-on customer implementations, in close partnership with Sales and Engineering. RESPONSIBILITIES - Partner with Sales on customer discovery calls (most often second calls, occasionally first calls for large accounts). - Lead demos and technical scoping to align on success criteria, architecture, and deployment approach. - Own benchmarking and repeatable deployments, including: - Handling standard deployment patterns and configurations across many modalities – LLMs, embeddings, image and video generation, Voice AI, etc. - Advising on tradeoffs like H100s vs B200s and latency-optimized vs throughput-optimized setups. - Driving consistent “playbook” style deployments for common models and use cases. - Become a power user of different runtimes such as vLLM, SGLang, and TRT-LLM and all the common configurations and tradeoffs between them - Drive POC and project execution, including: - Scoping POCs and keeping stakeholders aligned on timeline, deliverables, and next steps. - Acting as the “ringleader” or project manager for POCs. - Pulling in Forward Deployed Engineering (FDE) support when deeper or more complex technical work is needed. REQUIREMENTS - AI/ML background and the ability to credibly discuss AI/ML topics with technical stakeholders. - Strong customer-facing communication skills, including the ability to run structured discovery and clarify ambiguous requirements. - Technical depth to scope solutions, without needing to write production code. - Ability to script and prototype as needed, including comfort “vibe coding” to move quickly in technical workflows. NICE TO HAVE - Experience running or supporting benchmarks for ML inference deployments. - Familiarity with infrastructure tradeoffs relevant to inference performance and cost (for example GPU selection and latency versus throughput tuning). - Experience serving as a cross-functional technical lead for customer POCs, including coordination across Sales and Engineering. BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: USA - Remote Workplace: Remote About Us Since 2013, we’ve been building a CRM that gets out of your way and helps your team sell more, faster. Now we’re building AI into every part of it, so Close does the busywork and your team does the selling. No manual data entry, no 10-click workflows. Just communication-first, AI-powered sales software designed to help you succeed and scale. We're bootstrapped and profitable which means we answer to our customers and play by our rules. We're proud of our 120-person, 100% remote team, focused on building Close so that no small, scaling business fails because it can't figure out sales. ABOUT THE ROLE Close is a CRM built around the communication tools sales teams use every day: email, calling, SMS, workflows, reporting, and AI. Underneath that product is a broad technical surface — Python services and a large application backend, a TypeScript and React frontend, public APIs, Docker and Kubernetes, AWS infrastructure, and integrations with providers that handle sensitive customer data. Security work happens across it all today, but the ownership is spread across Engineering, Infrastructure, and Security & Trust. We’re hiring our first dedicated Product Security Engineer to make that work systematic. You’ll report to the Backend Platform team manager within EPD (Engineering, Product, and Design), while working across the entire product and infrastructure surface. You’ll find vulnerabilities, determine which findings matter most, and drive them through remediation. Often you’ll fix the problem yourself. Other times you’ll give the owning team a clear reproduction, a practical path forward, and enough context to prioritize correctly. You’ll analyze code, build proof-of-concepts, test running applications, tune or replace noisy tools, and automate the repetitive parts of vulnerability management. This is not a role where you forward scanner alerts and call the queue managed. Product and application security will be your responsibility. You’ll partner closely with our Infrastructure team on cloud security, access, and secrets, and with our Security & Trust Lead on GRC Engineering https://grc.engineering/, compliance (SOC 2) goals, audits, and corporate security. This role is a new one at Close. You’ll have significant room to decide where better tooling, clearer ownership, and a small amount of code can reduce the most risk. OUR STACK Our backend is primarily Python, with Flask and FastAPI services and TaskTiger https://github.com/closeio/tasktiger and Temporal handling much of our asynchronous work. We expose REST https://developer.close.com/ and GraphQL APIs and store data in MongoDB, PostgreSQL, Elasticsearch, and Redis. Our frontend is a large single-page TypeScript application built primarily with React. We bundle with Vite, target modern browsers, and test with Vitest, React Testing Library, Playwright, and Chromatic. The product updates in near real time and uses technologies including WebSockets and WebRTC. Our mobile application is built with React Native. We build and test Docker images in CI/CD and continuously deploy them to Kubernetes on AWS. Our infrastructure uses managed services including EKS, MSK, and ElastiCache, alongside services running on EC2. Terraform and Ansible automate much of the underlying infrastructure, and our containerized local development environment lets engineers run the full system on their own machines. For this role, our stack extends beyond simply backend or frontend: browser behavior, frontend state, API authorization, asynchronous processing, data access, third-party integrations, containers, and cloud configuration can all be part of the same attack path. We love open sourcing our code and ideas on our GitHub https://github.com/closeio and on The Making of Close https://making.close.com/, our behind-the-scenes Product & Engineering blog. Check out our open source projects like SocketShark https://github.com/closeio/socketshark, TaskTiger https://github.com/closeio/tasktiger, LimitLion https://github.com/closeio/limitlion and ciso8601 https://github.com/closeio/ciso8601. AI is both how we build and what we ship, and that's reshaped what engineering looks like. This is a transformation we’re embracing and find deeply exciting. YOU ARE - An application security engineer who writes code. You can move from reading an unfamiliar code path, to reproducing an exploit, to proposing or shipping a production-quality fix. Strong Python or TypeScript experience would be especially useful; fluency across both backend and frontend systems is even better. - Skilled at finding vulnerabilities conventional scanners may miss. You use modern AI-assisted review pipelines, guided by expert judgment, to uncover subtle flaws in web apps and APIs—from authentication, authorization, and tenant isolation to injection, SSRF, unsafe data flows, and business logic. You can threat-model designs, white-box review code, and test running systems. - Offensive-minded and operationally responsible. You know how to test like an attacker without being careless with customer data or production systems. You can turn a finding into a safe reproduction, assess exploitability and business impact, and retest the eventual fix. - An automation builder. You have worked with some mix of SAST, DAST, software composition analysis, container scanning, secrets scanning, or cloud posture tooling. More importantly, you know how to tune tools, connect them to engineering workflows, and remove noise. - AI-native and accountable. You use coding agents and LLMs to accelerate investigation, code review, and repetitive engineering work, but you verify their output. You think carefully about what happens when agents clone untrusted code, install dependencies, or receive access to credentials. - Able to separate severity from priority. A score is an input, not a foregone conclusion. You consider reachability, existing controls, customer impact, and attack chains, then explain the risk in language that is legible to an engineer or business owner. - Comfortable working across the business. You’ll collaborate with product engineers, Site Reliability Engineers, Security & Trust Lead, auditors, and external researchers without confusing partnership for pass-off ownership. You will follow findings to closure even when another team is responsible for the fix. - Self-directed in a remote environment. You can take an ambiguous surface (say, secret rotation or dependency remediation) and learn how it works across multiple systems then turn it into a practical plan with measurable progress. You do not need to arrive as the deepest expert in every part of this scope. You do need to be able to investigate an unfamiliar system, determine what matters, and bring the right people with you. YOU WILL The work spans hands-on application security, security automation, vulnerability management, and infrastructure partnership. Depending on where you find the greatest risk and leverage, projects could include: - Build a recurring product security review program. Threat model new features, audit high-risk areas, review code, and build safe proof-of-concepts in isolated development environments. Work across our backend, frontend, APIs, and customer-facing integrations. - Improve application security testing. Combine static analysis, dependency and secrets scanning, dynamic testing in development, and carefully scoped production testing. Use existing tools where they fit and build focused automation where they don’t. - Own vulnerability intake and remediation. Triage findings from HackerOne, scanners, penetration tests, audits, customers, and internal research. Reproduce issues, assess exploitability and impact, track remediation, and verify fixes. Serve as technical lead for our bug bounty program while contract and budget ownership remain elsewhere. - Turn security alerts into useful engineering work. Verify scanner coverage and automate ingestion, deduplication, enrichment, prioritization, and routing—so teams spend less time interpreting alerts and more time fixing important issues. - Make dependency remediation safer and less manual. Improve scanning across our Python and TypeScript codebases, then build workflows to assess upgrades, stage pull requests, run checks, and route work without exposing credentials to untrusted packages or build steps. - Make secrets routinely rotatable. Partner with service owners and Infrastructure to inventory application secrets, add graceful rotation paths, document provider-specific runbooks, and automate rotation where the provider and risk justify it. Expand our use of Vault-backed dynamic credentials and reduce the number of rotations that require a coordinated fire drill. - Strengthen AWS security with Infrastructure. Evaluate and improve automated detection of risky configuration across identity, networking, compute, storage, containers, and registries. Turn findings into secure defaults, just-in-time access patterns, infrastructure guardrails, and actionable remediation—not build a second Infrastructure team. - Support audits and raising the security floor. Partner with Security & Trust on external assessments, provide technical context, and ensure findings are fixed rather than rediscovered. Along the way, create documentation, paved roads, and lightweight training that helps engineers make safer choices without waiting for a security review. - Take a key technical role in security incident response. Partner with Engineering and Infrastructure to coordinate investigation, containment, and remediation. Contribute to root-cause analysis and follow-up improvements, translating lessons learned into stronger controls and reduced recurrence. Tech you’ll touch: Python, TypeScript, React, Flask, FastAPI, GraphQL, Docker, Kubernetes, AWS, Vault, GitHub Actions, MongoDB, PostgreSQL, Redis, Kafka, Elasticsearch and the security tooling you help us choose. BENEFITS - Compensation: Competitive pay plus an organization-wide goal-based bonus - Paid Time Off: ~5 weeks of PTO to start. Plus a 1-week all-company Winter Holiday Break and paid US holidays. You'll earn 2 extra days for every year you're with Close. - 80% Work Option: Work with your manager to choose between a standard 5-day week or a 4-day week at 80% pay - Parental Leave: Paid leave for primary and secondary caregivers - Sabbatical: A 1-month paid sabbatical every 5 years with the team - Healthcare (US residents): Two medical plans with Close covering the majority of your premium, plus Dental, Vision, HSA, FSA, and company-paid Long-Term Disability - 401k (US residents): We match your contributions up to 6%, vested immediately OUR VALUES Build a house you want to live in - Examine long-term thinking and action No BS - Practice transparency and honesty, especially when it’s hard Invest in each other - Build successful relationships with your coworkers and customers Discipline equals freedom - Keep your word to yourself and others Strive for greatness - Constantly challenge yourself and others LEARN MORE Listen to our CEO and Founder, Steli Efti, tell the story of Close’s journey in the $0-30m Blueprint https://www.close.com/blueprint.  Watch our culture video https://www.youtube.com/watch?v=maXKi1GN2MI from our 2023 team retreat in Milan. Every year our entire team gathers in person to build connection, foster cross-functional collaboration, and have fun. In 2027, we're headed to Dusseldorf, Germany! Explore our product. Check out a demo https://www.close.com/demo-site! OUR HIRING PROCESS We ask a few role-specific questions as part of our application process. These questions are designed to help us learn more about you from the start, so please answer each one thoughtfully. We see this as an opportunity to get to know you beyond your resume. We use AI tools daily at Close and expect candidates to do the same. In evaluating your application, we aim to get a sense for you - the way you think, how you communicate, the work you've done. Applications that read as fully AI-generated will not be considered. Regardless of fit, you can expect to hear back from our team with an update on the status of your candidacy. If you progress to the interview process, you'll receive a full outline of the role-specific steps in your first touchpoint with us. We do our best to make the hiring process clear and human.

Location: Foster City, CA Workplace: Hybrid 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. Join us at the forefront of AI and cloud-native security as we work to secure one of the most innovative developer platforms in the world. As the Cloud Security Lead, you will shape the cloud and infrastructure security program that protects millions of developers, enables safe AI-assisted development, and ensures organizations can confidently bring our platform into enterprise environments. In this role, you will own cloud security across GCP (primary) and supplemental environments in AWS and Azure, as well as containerized systems, SaaS platforms, and our multi-tenant AI infrastructure. You’ll improve our security posture through strong architecture, posture management, secure-by-default development practices, and close partnership with Engineering, Compliance, Security Architecture, and Platform teams. This is a highly impactful, hands-on leadership role—perfect for someone who wants to solve complex security challenges at scale while influencing product, engineering, and go-to-market teams. WHAT YOU’LL DO: CLOUD SECURITY ENGINEERING - Lead configuration hardening across GCP, with additional oversight of workloads and integrations running in AWS and Azure. - Own and optimize CSPM platforms across multi-cloud environments—establishing configuration baselines, guardrails, and remediation workflows. - Secure critical SaaS platforms, ensuring proper configurations, access controls, and engineering integrations. - Lead infrastructure vulnerability management across multi-cloud systems, containers, registries, and platform services. - Enhance security across containerized and Kubernetes (GKE/EKS/AKS) workloads, including runtime protections, network policies, and workload identity. - Assess secure logging configurations across cloud/SaaS providers, ensuring audit logs, retention, and routing meet monitoring and architecture needs. SECURE DEVELOPMENT & ARCHITECTURE ENABLEMENT - Partner with engineering teams to make services secure by default, embedding security into development workflows, CI/CD pipelines, and cloud-native deployments. CROSS-FUNCTIONAL RESPONSIBILITIES - Collaborate with Security Monitoring, Compliance/GRC, Architecture, DevOps, Platform Engineering, and ML Infrastructure. - Participate in communicating security advisories, best practices, and updates to Replit’s customers. - Support incident investigations as a cloud security subject-matter expert. REQUIRED SKILLS & EXPERIENCE: - 7+ years of experience in cloud engineering, with 3+ years in a senior or lead role. - Hands-on experience with CSPM tools (Wiz, Lacework, Prisma, Orca, SCC, etc.). - Deep expertise in GCP security (IAM, VPC, KMS, GKE, Cloud Logging). - Experience securing and governing SaaS platforms and identity integrations. - Operational experience with infrastructure vulnerability management across cloud and container environments. - Working knowledge of AWS and/or Azure security services and configurations. - Experience with container and Kubernetes security across GKE, EKS, or AKS. - Strong IaC security experience with Terraform, Pulumi, or similar tooling. - Familiarity with compliance standards (SOC 2, ISO 27001, PCI DSS). PREFERRED QUALIFICATIONS: - Experience supporting engineering teams in building secure-first, cloud-native or PaaS environments. - Background securing AI/ML pipelines, model-serving infrastructure, or developer platform services. - Experience in high-growth technology or cloud-native product companies. - Experience with securing AI/agentic systems and sensitive data pipelines. - Automation/scripting with Python. - Relevant certifications (e.g., GCP Professional Cloud Security Engineer, AWS/Azure security certs). WHAT WE VALUE: - Problem-solving mindset — Ability to break down complex security and operational challenges into clear engineering solutions. - Autonomy — Comfortable leading initiatives, collaborating effectively, and driving outcomes with minimal oversight. - Communication excellence — Able to translate deep technical concepts for engineers, executives, and enterprise customers. - Continuous learning — Passion for staying current with AI security, cloud-native advances, and emerging threats. - Automation-first approach — Belief in reducing operational toil and building scalable, self-healing systems. This is a full-time role that can be held from our Foster City, CA office. The role has an in-office requirement of Monday, Wednesday, and Friday. Full-Time Employee Benefits Include: 💰 Competitive Salary & Equity 💹 401(k) Program with a 4% match (US Only) ⚕️ Health, Dental, Vision and Life Insurance 🩼 Short Term and Long Term Disability 🚼 Paid Parental, Medical, Caregiver Leave 🏝 Flexible Time Off (FTO) + Holidays 🚗 Commuter Benefits (In-Office & US Only) 📱 Monthly Wellness Stipend 🧑‍💻 Autonomous Work Environment 🖥 In Office Set-Up Reimbursement (In-Office Only) 🚀 Quarterly Team Gatherings ☕ In Office Amenities (In-Office Only) Want to learn more about what we are up to? - Self-driving Company https://replit.com/blog/self-driving-company - Replit Agent at Scale https://replit.com/blog/evaluating-and-improving-agent-at-scale - AI Adoption https://replit.com/blog/ai-adoption - Build Open-Source Apps https://replit.com/build/open-source-app-builder   Interviewing + Culture at Replit - Operating Principles https://blog.replit.com/operating-principles - Reasons not to work at Replit https://blog.replit.com/reasons-not-to-join-replit To achieve our mission of making programming more accessible around the world, we need our team to be representative of the world. We welcome your unique perspective and experiences in shaping this product. We encourage people from all kinds of backgrounds to apply, including and especially candidates from underrepresented and non-traditional backgrounds.

Location: San Francisco; Boston; Seattle; New York Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! SENIOR ACCOUNT EXECUTIVE - TECHNOLOGY Why this role? In this role, you will have ownership of the full sales cycle - from identifying leads to closing deals with Global 2000, large enterprises within the Technology sector. We're looking for an approachable and compelling communicator who loves working with prospects to uncover their needs and feels comfortable developing tailored value propositions around how Cohere's platform can help them achieve their business goals. You'll lay the foundation for Cohere's growth by owning your territory and collaborating with teammates across customer success, sales development, marketing, and solution architecture. You'll be the voice of the field and help our product and engineering teams prioritize the Cohere roadmap with customer-centric care. It's a highly self-directed role, so you should be someone who thrives in an unstructured and quickly evolving environment. And your opportunity for impact will be astronomical — Cohere has skies-the-limit potential, and you'll help us reach it. As an Account Executive focused on the Technology sector you will: - Focus on net-new logo acquisition via outbound activity and relationship building with key stakeholders while also bringing a strong network of key decision-maker and influencer contacts and relationships in the vertical to accelerate engagements, drive strategic partnerships and win sales opportunities - Work closely with customers and prospects as a consultative, trusted advisor who deeply understands their challenges and goals, their technology ecosystem, and will tailor solutions to drive measurable impact for their businesses - Work in close partnership with channel partners to find opportunities to scale outreach and customer satisfaction in your region - Collaborate with product and engineering teams as well as customer success on strategic motions to deliver solutions to large enterprise customers - Collaborate with Sales Development Representatives to drive top of funnel activity - Own the full sales cycle – from initial outreach through proof-of-concept, deal close, and deployment; this is not a transactional sale that you can walk away from after the contract is signed but rather requires ongoing oversight of the project to ensure success You may be a good fit if you have: - 8-12+ years of previous B2B sales experience with Global 2000, large enterprises in the Technology sector, negotiating and closing transformational multi-year (2-5 year) SaaS deals in the 7 figure range, and a track record of high performance and exceeding quota - Previous experience as a technical consultative salesperson, selling complex products, such as developer tools, API products, or AI / NLP solutions, are a plus, with a focus on applications in the Financial Services sector - Previous experience working with customers during the deployment phase of the engagement, aligning on how best to configure and customize the solution that supports success in production and builds trust to set up for expansion and growth - Previous experience working with channel partners such as cloud hyperscalers and system integrators to drive sales cycles and hit shared revenue goals - High tolerance for ambiguity - as an early sales hire, you'll have to be a self-starter, doer and a strategist who is capable of wearing many hats and doing what it takes to figure out a path to success - Curiosity - you want to go deep on NLP and become an expert on our technology while considering how to fit into a large organization's technology landscape with a focus on its applications in the Financial Services sectors - Fantastic communication skills - you are a great listener, have a knack for understanding what matters most to others, build strong relationships, can speak to the c-suite, and feel comfortable speaking to both technical and non-technical audiences in the Financial Services sector Additional Requirements: - Deep understanding of the Technology industry, including key trends, challenges, and opportunities - Ability to articulate the value of AI and NLP solutions in the context of Financial Services operations. FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: United States & Canada Workplace: Remote About WorkOS 🚀 WorkOS builds modern developer tools and APIs that make it easy for companies to become Enterprise Ready. Our platform powers authentication, identity, authorization, and other critical infrastructure that developers need to securely scale their products to large organizations. We recently raised a $100M Series C, valuing the company at $2B, led by Meritech and Sapphire with participation from Greenoaks, Craft, Abstract, and Audacious. WorkOS powers enterprise features for many of the fastest-growing AI companies, including OpenAI, Cursor, and Perplexity, Sierra, and Plaid. As AI reshapes software, WorkOS is at the frontier of Human and Agent Authentication, Identity, and Access Control helping companies answer a new critical question: who are your agents, and what are they allowed to do? Our fast-growing customer base includes hundreds of modern software companies building the next generation of enterprise-ready products. ABOUT THE ROLE The Data team at WorkOS plays a central role on the company operations to ensure information and insights are accurate and available from any surface, whether that's a visualization tool or an agent's response, to accelerate company growth and scale. The team owns WorkOS's internal data platform end to end: ingestion, orchestration, the Snowflake warehouse, dbt transformations, governance and access controls. We also own the consumption layer: the reverse-ETL syncs that land data in Salesforce and Slack, the semantic views that agents query, the definitions that keep reporting consistent across the company, and the visualization tooling the company uses (ask us about Flashboards https://workos.com/blog/reporting-tool-with-no-editor). We run on an agent-first operating system: we are a lean team that moves fast, we document so agents can execute, and AI agents query the warehouse, run our runbooks, and open pull requests alongside us. We trust each other's expertise, we work out loud and in the open, and not opposed to rapid experimentation to get to the right solution for the business. We're hiring a Data Engineer to own and evolve the systems that move, transform, protect, and serve data across our internal warehouse. This is a high-ownership role on a lean team: you will be the DRI for the platform and its core data models, partner directly with Product Engineering, RevOps, Finance, GTM Engineering, and Security, and raise the bar on reliability, correctness, and operational rigor. The role spans the platform and what runs on it. You will own ingestion, orchestration, and access governance; the dbt models and metric definitions that depend on them; and how AI is applied across the data stack, so that trusted data is easy for both people and AI agents to discover, understand, and work with. You don't need to have done this exact job before. The best data engineers at WorkOS are the ones who notice in a Slack thread that a number doesn't match, trace it from the dashboard through the Gold model to the connector, fix the connector, and confirm the definition with its owner before the weekly review. When a business team asks for a field in Salesforce, they don't hand it off; they build the model, write the sync, and add the test. They would rather automate the runbook than run it a third time. They enjoy collaboration with different parts of the business and can find simple, scalable solutions to ambiguous problems. If that sounds like how you work, we want to talk. RESPONSIBILITIES - Own the reliability, freshness, and scaling of the ingestion and orchestration pipelines that land source data in Snowflake, including monitoring, alerting, runbooks, and backfill and reprocessing patterns - Design, build, and scale the core dbt models (Bronze, Silver, Gold) for billing and usage, CRM, product events, and GTM funnel reporting - Partner with Product, Finance, RevOps, and GTM to define metrics and codify them in the warehouse, and diagnose and resolve data quality and freshness issues at source, not just downstream - Own Snowflake RBAC, dynamic masking, and PII classification for humans, agents, and service accounts, so sensitive data is protected without blocking legitimate use, and review DDL and access requests from Engineering and GTM - Own the reverse-ETL layer and the runbooks that deliver warehouse data to Salesforce, Slack, and internal agents - Extend the semantic views, context, and evaluations that let agents answer business questions accurately, and expand what agents can operate directly, from runbooks and ingestion to pull requests - Build and advance the CI/CD review gates in the data-platform monorepo, including the automated review that agent-authored pull requests pass through - Own the infrastructure the data platform runs on: the compute, deployments, secrets and access patterns, and environments behind ingestion and orchestration, with attention to availability and failure modes, in partnership with our infrastructure engineers Example problems you might work on, possible paths rather than a fixed roadmap: - Standardizing how Postgres and SaaS sources are ingested, and consolidating end-to-end pipeline deployment and orchestration in Prefect - Managing Snowflake RBAC, resource management, and masking policies as code with Terraform - Using query history to improve analytics tables and semantic views, and to keep agent answers accurate and consistent as data grows and metrics shift - Automating masking coverage as new data sources arrive, so adding a new table no longer needs a human in the loop - Automating near-certain matches in the Identity Graph - Pseudonymizing product data in the ingestion path, alongside compliance and data-deletion policies - Extending transcript aggregation across sources, including PII detection before transcripts enter the warehouse - Building the reverse-ETL framework and runbooks that deliver data to other tooling and agents - Running self-hosted data services on Kubernetes and managing their AWS resources (IAM, storage, secrets) as code with Terraform QUALIFICATIONS - 5+ years (or equivalent) building and operating production data platforms, including the transformation layer - Deep experience with Snowflake, dbt, and an orchestrator such as Prefect, Airflow, or Dagster, and with ingesting data from production databases and SaaS sources, including backfill and reprocessing patterns - Experience running data systems in production: monitoring, alerting, debugging, incident response habits, and pragmatic SLO/SLA thinking - Experience with warehouse access governance: RBAC, masking policies, and PII handling - Strong data modeling judgment and an understanding of schema evolution - Strong SQL and Python; disciplined engineering practices (tests, docs, reviews, CI/CD) - Proven experience operating as the only engineer on a layer, balancing foundational architecture with urgent business needs - Working knowledge of how GTM, Finance, and Product teams operate in addition to working with Engineering, and experience translating ambiguous business questions into technical specs - Comfortable using LLMs and coding agents as part of your day-to-day development workflow, with the judgment to validate their output and scale it into shared processes, and embracing AI and automation to scale platform work and accelerate your teammates - A systems thinker who reasons carefully about freshness, correctness, and failure modes, especially for data that everything else depends on - Pragmatic: you start with the simplest solution that works, prove it, then scale it, and you balance fast answers with durable solutions - You look for where AI can remove a bottleneck for the people and agents who depend on the warehouse, and you build the durable tools and workflows they rely on every day Benefits and Perks (US Only) 💖 At WorkOS, we offer resources that emphasize personal and familial well-being. We offer healthcare coverage for you and your family, including medical, dental, and vision. We offer parental leave, paid-time off and fully remote working arrangements.   - 401k matching - Competitive Equity - Healthcare, dental and vision coverage - FSA, ST/LT Disability, Voluntary Life - Carrot fertility benefits - 20 days paid vacation + 10 holidays + unlimited sick leave - 12 weeks fully paid parental leave - Fitness: Monthly stipend for gyms, yoga classes, race registrations or whatever keeps you active - Wellness: Monthly stipend for a massage, meditations class, therapy, or activities that enhance your well-being - Commuter benefits for hybrid employees in SF/NYC - Unlimited token usage! Please inquire directly with our recruiting team for benefits available to those working outside the US.   Equal Opportunity Employer WorkOS is an equal opportunity employer, committed to diversity and inclusiveness. We will consider all qualified applicants without regard to race, color, nationality, gender, gender identity or expression, sexual orientation, religion, disability or age. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Design, implement, test, and operate production services and APIs. Lead projects or meaningful components of projects from problem definition through deployment and iteration.

145 500 – 235 400 $

Location: San Francisco; Toronto; New York; Montreal; Seattle Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We're looking for distributed systems engineers and product-minded generalists to build the distributed runtime that powers large-scale LLM inference on Baseten. Our inference platform empowers customers to deploy and operate cutting-edge models with industry-leading performance, scalability, and reliability. It also powers Model APIs, our hosted endpoints for the latest open-source models. You'll work across the stack, from the developer experience customers use to deploy models, through the libraries behind features like tool calling and reasoning, down to the systems that orchestrate deployments on Kubernetes and route traffic efficiently. Your job is to make sure every model on our platform is fast, reliable, and cost-efficient. You'll join a small, high-impact team at the intersection of distributed systems, model performance, infrastructure, and product, helping define how developers use AI models at scale. This role is ideal for engineers who enjoy owning systems in production, solving hard integration problems, and making complex infrastructure simple and reliable for users.   EXAMPLE INITIATIVES You'll get to work on these types of projects on our Inference Platform: - The Baseten Inference Stack at NVIDIA Dynamo Day https://www.baseten.co/blog/nvidia-dynamo-day-baseten-inference-stack/ - 2x faster inference with KV cache-aware routing https://www.baseten.co/blog/how-baseten-achieved-2x-faster-inference-with-nvidia-dynamo/ - How Baseten multi-cloud capacity management (MCM) unifies deployments https://www.baseten.co/blog/how-baseten-multi-cloud-capacity-management-mcm-powers-cloud-self-hosted-and-hybr/#comparing-deployment-options-cloud-vs-self-hosted-vs-hybrid RESPONSIBILITIES - Build the infrastructure and orchestration systems that deploy and run large-scale distributed LLM inference, including routing, autoscaling, scheduling, and runtime management. - Design, build, and operate Model APIs, with a focus on advanced inference capabilities: structured outputs (JSON mode, grammar-constrained generation), tool/function calling, and multimodal serving. - Implement platform fundamentals such as API versioning, validation, usage metering, quotas, and authentication. - Instrument deep observability (metrics, traces, logs) and build repeatable benchmarks for speed, reliability, and quality. Help set best practices for testing, release automation, and operational excellence. - Debug and harden complex production systems spanning Kubernetes, distributed runtimes, networking, and GPU workloads to improve reliability and scalability. - Partner with Inference Performance engineers and other teams to make new optimizations broadly available to customers and easy to configure. - Own projects end to end, from architecture through deployment, monitoring, and iteration on customer feedback. Along the way, make thoughtful tradeoffs between performance, reliability, operational simplicity, and developer experience.   REQUIREMENTS - Bachelor's, Master's, or Ph.D. in Computer Science, Engineering, or a related field, or equivalent practical experience. - 3+ years building and operating distributed systems, backend infrastructure, or large-scale APIs where reliability, latency, and scale are first-class concerns. - A proven track record of owning low-latency, reliable backend services, including rate limiting, auth, quotas, metering, and migrations. - Infrastructure instincts with a feel for performance: profiling, tracing, capacity planning, and SLO management. - Comfort debugging performance and reliability issues across multiple layers of the stack, from application behavior down to runtime and infrastructure internals. - A strong sense of developer experience. You think about how systems are used, not just how they work. - Eagerness to learn new languages, frameworks, and systems, and a real interest in inference engineering. Prior ML or LLM experience isn't required, though experience with model serving or inference systems is a plus. - Excellent written communication and collaboration skills, including writing clear design docs and working across functions.   NICE TO HAVE - Experience with or contributions to LLM inference engines and frameworks such as vLLM, SGLang, TensorRT-LLM, TGI, or Dynamo. - Deep Kubernetes experience, including operators and custom resources, plus familiarity with service meshes or API gateways. - Experience with distributed scheduling, autoscaling, or service orchestration. - Experience operating GPU workloads in production. - A background in developer-facing infrastructure or APIs, or contributions to open-source infrastructure or ML systems. - Familiarity with observability tooling, CI/CD systems, or release automation. BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: San Francisco; Toronto; New York; Montreal; Seattle Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We're looking for inference performance engineers who want to make the world's most demanding AI workloads run faster and more efficiently. You'll work across the stack, from the inference engine and runtime through scheduling, serving, and routing. Along the way you'll apply techniques like prefill/decode disaggregation, speculative decoding, and KV-cache management. You'll reason from first principles about where time and memory go, find what's holding performance back, and close the gap. Your work directly impacts how fast our customers' models run and how efficiently we serve them. This role is ideal for someone who thrives in a fast-paced startup environment and is eager to make significant contributions to the exciting field of LLM inference.   EXAMPLE INITIATIVES You'll get to work on these types of projects as an Inference Performance engineer: - Agentic Kernels in Production https://www.baseten.co/blog/agentic-kernels-in-production/ - How we built the new fastest API for GLM-5.2 https://www.baseten.co/blog/how-we-built-the-new-fastest-api-for-glm-52/ - Live draft model training for speculative decoding https://www.baseten.co/blog/live-draft-model-training-for-speculative-decoding/#eliminating-traditional-bottlenecks - Making Kimi K3 Tokenization 18x faster https://www.baseten.co/blog/making-kimi-k3-tokenization-18x-faster-for-million-token-agentic-workloads/ - The Baseten Inference Stack https://www.baseten.co/resources/guide/the-baseten-inference-stack/ - Driving model performance optimization https://www.baseten.co/blog/driving-model-performance-optimization-2024-highlights/ RESPONSIBILITIES - Implement and productionize cutting-edge inference techniques, working deep in runtime internals. That includes quantization, speculative decoding, KV-cache reuse, chunked prefill, LoRA, guided generation for structured outputs, and custom scheduling and routing algorithms. - Profile and optimize inference end to end, from kernel launch overhead and memory layout up to request scheduling, prefill/decode disaggregation, and cache-aware routing. Run cross-layer investigations, such as tracing a tail-latency regression from request timing through routing and batching down to a kernel. - Turn performance into cost savings. Improve tokens per GPU-hour, raise utilization, and give customers and internal teams clear latency/throughput/cost tradeoffs. - Bring up and tune new model architectures on new hardware quickly, often in the same week they're released. - Build benchmarking frameworks that measure real-world performance across model architectures, batch sizes, sequence lengths, and hardware configurations. - Contribute upstream to open-source inference engines (vLLM, SGLang, TensorRT-LLM), and partner closely with model, infrastructure, and customer-facing teams to ship wins.   REQUIREMENTS - Bachelor's, Master's, or Ph.D. degree in Computer Science, Engineering, Mathematics, or related field. - Experience with one or more general-purpose programming languages, such as Python or C++. - Familiarity with LLM optimization techniques (e.g., quantization, speculative decoding, continuous batching). - Strong familiarity with ML libraries, especially PyTorch, TensorRT, or TensorRT-LLM. - Demonstrated interest and experience in LLMs. - Deep understanding of GPU architecture.   NICE TO HAVE - Proficiency in enhancing the performance of software systems, particularly in the context of large language models (LLMs) - Contributed to vLLM, SGLang, TensorRT-LLM, or another inference engine. - Worked on large-scale distributed serving: autoscaling, load balancing, multi-region or multi-cloud capacity. - Written or optimized GPU kernels (CUDA, Triton, CUTLASS, or similar) - Worked on quantization (FP8/FP4, AWQ, GPTQ) or speculative decoding in production. - Deep understanding of software engineering principles and a proven track record of developing and deploying AI/ML inference solutions. BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: Remote About the Team: Netlify’s Data team helps the company understand and improve the full product-led growth journey, from activation and engagement through conversion, retention, and monetization. We partner closely with Product, Engineering, and Growth to uncover opportunities, evaluate investments, and understand what drives customer and business outcomes. We’re hiring a Senior Staff Data Scientist to deepen how data shapes our product and growth strategy. You’ll develop an end-to-end understanding of the PLG journey, proactively identify opportunities, and turn complex data into hypotheses, experiments, and recommendations that influence where we invest and what we build. This is a highly autonomous role for someone who can move from identifying an important question to shaping the approach, defining success, and driving toward an answer. What You'll Do: Own the analytical understanding of Netlify’s PLG performance across activation, engagement, conversion, monetization, and retention, identifying opportunities before they become requests Partner with Product and Engineering leadership to turn behavioral insights into product bets, defining what to test, how to measure it, and what the results mean Lead experimentation from hypothesis through decision, including study design, methodology, success metrics, guardrails, analysis, and recommendations Apply statistical rigor where it matters while recognizing when there is enough signal to make a decision and move forward, and help teams develop that same judgment Build scalable analytical systems like semantic models, trusted metrics, proactive monitoring, and AI-powered agents  that surface opportunities without waiting to be asked Use AI to investigate faster, automate recurring analytical work, and test more hypotheses without sacrificing the judgment that makes the output useful Identify gaps in measurement, event instrumentation, and metric definitions, and partner with Data and Product Engineering to close them Serve as a trusted analytical partner to PLG leadership, using evidence and product judgment to influence investment decisions and roadmap priorities Influence product strategy through evidence, product instincts, and a clear point of view, without relying on formal authority to do it What You'll Bring: 8+ years of experience in product analytics, growth analytics, or data science, with a track record of high ownership and measurable impact on PLG or consumer product outcomes Deep understanding of product and growth dynamics across activation, engagement, conversion, monetization, and retention Demonstrated ability to turn behavioral data into product hypotheses and carry them from insight through experimentation and measured outcomes Deep experimentation expertise: study design, statistical reasoning, causal inference, and the judgment to know when an experiment has told you what you need to know Experience building analytical systems such as metrics layers, monitoring frameworks, or semantic models that teams can rely on over time An AI-native approach to analysis: you use AI tools actively to accelerate investigation, automate repetitive work, and surface patterns faster A track record of influencing senior stakeholders and product direction through analytical reasoning, clear recommendations, and sound judgment Comfort operating with significant autonomy in ambiguous problem spaces, including determining which questions are most important to answer Strong written and verbal communication skills in distributed environments, with the ability to make complex findings clear and recommendations actionable This Role is a Great Fit If: You're energized by finding the opportunity before anyone thought to ask - proactive discovery is how you naturally work, not a mode you shift into You think like a product person who happens to be exceptionally rigorous with data, not a data person who occasionally weighs in on product You thrive when the problem isn't handed to you - you'd rather define the question worth asking than answer the one that landed in your queue You get excited about building systems that keep working after you've moved on to the next problem You're comfortable making a call with imperfect information and can articulate clearly why you made it You enjoy being a thought partner to senior leaders - shaping how they think about investment and opportunity, not just supporting decisions already made You work well in a remote-first, async environment where written clarity and self-direction matter more than proximity You're drawn to roles where the measure of success is outcomes, decisions made, bets tested, metrics moved, not volume of output produced Applying Not sure you meet 100% of our qualifications? Please apply anyway! When applying please include: A resume or short listing of your job history & skills (link to a LinkedIn profile would be fine). We appreciate a cover letter explaining why you would enjoy working in this role at Netlify to get to know you a bit better, though this is not required and will not impact your application. Our mission is to “build a better web” and that cannot be done without a diversity of skill sets, backgrounds and thoughts. Of everything we've ever built at Netlify, we are most proud of our team. Netlify is an Equal Opportunity Employer. We are devoted to building a team of people with diverse backgrounds and lifestyles. Driving equality empowers our team, enables us to innovate, and helps us maintain a more inclusive environment. We don’t discriminate against employees or applicants based on gender identity or expression, sexual orientation, religion, age, race, military/veteran status, citizenship, pregnancy status, or any other differences. If we can do anything to provide a better interview, i.e. accommodate a disability, then please let us know by emailing accommodations@netlify.com . About Netlify Netlify is the most popular way to build, deploy, and scale modern web applications, empowering everyone from fast moving solo developers to enterprise teams. Millions of developers and organizations rely on Netlify as their platform of choice for composing web applications that are production ready, performant, and flexible. Now, as we embrace the next era of software development, we are embedding the same fluid, intuitive experience into the Agent Experience (AX), making it just as simple for intelligent agents to understand, interact with, and act on our platform as it is for developers. Whether your user is human or machine, Netlify ensures the path from idea to URL is seamless, fast, and deeply reliable. We are a Series D company that has raised over $200M from investors such as Andreessen Horowitz, Kleiner Perkins, EQT, Bessemer, BOND, and Menlo Ventures. As a fully distributed company, we aim to create a company culture where the best idea can come from anywhere and strive to be thoughtful, compassionate, and collaborative in our work. If this sounds like something you’d like to be part of, we’re excited to connect with you! At Netlify, we are committed to a compensation philosophy that prioritizes fairness and equity, positions our employee compensation competitively in the market, recognizes and rewards performance, and takes a comprehensive approach to our rewards package. We anchor our compensation philosophy on a market-based approach, therefore salary ranges may differ depending on the labor cost in a particular location. The salary provided is in addition to robust benefits and participation in Netlify’s equity plan. Our hiring range for this role is targeted at $204,000 - $275,000 for most US-based locations.  Candidates outside the US or in premium markets should consult with their Talent Acquisition partner regarding location-based ranges, as they may be higher or lower than the average US range listed. The starting pay will be determined based on multiple factors, including expertise and skills, market demands, experience, internal equity, and applicable geographic location. These compensation packages and ranges are subject to change and may be modified in the future.

Location: Berlin Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? As a Senior Account Executive at Cohere you will have ownership of the full sales cycle - from identifying leads to closing deals, with Defense, Federal Civilian and Local Government Agencies in Germany. In this role you will be focussed on business development activity across all PUBSEC Government Agencies and Departments in Germany. We’re looking for an approachable and compelling communicator who loves working with public sector customers to uncover their needs and feels comfortable developing tailored value propositions around how Cohere’s platform can help them drive better mission and citizen outcomes. You’ll lay the foundation for Cohere’s growth by owning your territory and collaborating with teammates across Customer Success, Sales Development, Marketing, and Sales Engineering. You’ll be the voice of the field and help our Product and Engineering teams prioritize the Cohere roadmap with customer-centric care. In this highly self-directed role, you will thrive in a quickly evolving environment. As a Senior Account Executive, you will: - Drive net-new customer acquisition through targeted outbound activity, senior leader engagement, and relationship building in Germany. - Develop and execute a sales plan for Germany, prioritizing accounts and opportunities through collaboration with Cohere leadership. - Act as a trusted advisor and thought partner to public sector customers and prospects by understanding their goals and shaping AI solutions that deliver measurable value - Work closely with channel and regional partners, as well as major system integrators to scale outreach, accelerate adoption, and maximize customer success - Leverage senior-level relationships with executives and government decision-makers to drive strategic opportunities and long-term partnerships - Collaborate with Product and Engineering teams on strategic efforts to deliver enterprise and public-sector solutions - Partner with SDRs and Marketing to drive top-of-funnel activity and overall territory growth - Own the full sales cycle; including discovery, technical and business validation, proof-of-concept, procurement, and deal close within a team-selling environment You may be a good fit if you have: - 10+ years of direct public sector sales experience in Germany, with a proven track record of closing $3M+ annual quotas. - Deep knowledge of PUBSEC procurement and budget cycles, decision-making processes, and how to work with regional partners and resellers. - Established network in Germany, including federal agencies, prime contractors, and industry associations. - Experience selling SaaS, AI/ML, or enterprise software solutions to government clients. - High tolerance for ambiguity, you are both a strategist and a hands-on operator capable of building a market from the ground up - Strong organizational skills, with the ability to manage multiple internal and external stakeholders across fast-moving deals - Creativity and strong technical acumen to structure unique, mutually beneficial partnerships - Excellent communication skills, you listen deeply, understand what matters to senior decision-makers, and confidently present to both technical and non-technical audiences. - English and German language proficiency essential. - Must be based in Germany with willingness to travel (25-35%). FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: San Francisco Workplace: OnSite ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: Modal’s Inference Runtime team owns the container runtime stack used to run inference and training workloads across our fleet. We work at the boundary of Linux, containers, filesystems, storage, GPU drivers, and distributed systems.Our goal is to make demanding ML workloads start quickly, run efficiently, and remain securely isolated — whether they use a single GPU, hundreds of gigabytes of memory, or multiple GPUs connected with RDMA.We’re looking for a systems engineer who enjoys working deep in the stack. You’ll build production runtime infrastructure in Rust and Go, diagnose difficult Linux and performance problems, and help determine the architecture of Modal’s container platform. You’ll also work closely with maintainers of gVisor and contribute to the runtime itself when the right fix belongs upstream. THE WORK: - Make container startup, checkpoint, and restore dramatically faster for large inference and training workloads. - Build multi-GPU and accelerator-aware snapshotting, including efficient handling of GPU memory and RDMA-enabled workloads. - Design zero-copy and low-copy data paths between container memory, filesystems, storage, and Modal’s runtime. - Optimize large snapshot pipelines using techniques such as parallel uploads, direct I/O, incremental snapshots, and more efficient memory handling. - Improve container image and filesystem performance across EROFS, FUSE, page caches, overlay filesystems, and remote storage. - Extend our sandboxed runtime to support new GPUs, drivers, profiling tools, and device capabilities across NVIDIA and AMD hardware. - Debug complex failures involving system calls, virtual memory, process lifecycle, kernel behavior, GPU drivers, and container isolation. - Safely roll out runtime and kernel changes across a heterogeneous fleet using compatibility controls, scheduling constraints, feature flags, and observability. - Work across the runtime, scheduler, storage, and GPU infrastructure—and take ambiguous production problems from investigation through deployment. WHAT WE’RE LOOKING FOR: - Strong Linux systems knowledge, particularly processes, virtual memory, filesystems, system calls, scheduling, namespaces, cgroups, and signals. - Experience building or debugging container runtimes, sandboxes, Linux kernel, or similarly low-level infrastructure. - Strong programming ability in Rust, Go, or another systems language, with an interest in becoming productive in both Rust and Go. - Experience profiling and improving systems where memory movement, I/O, synchronization, or kernel interactions dominate performance. - Comfort debugging across abstraction boundaries, from application behavior down through runtimes, drivers, and the kernel. - An ability to turn loosely defined production problems into well-designed, reliable systems. - A desire to own important infrastructure and work closely with both internal teams and customers. RELEVANT EXPERIENCE: Any of the following would be helpful, but none is required: - gVisor, runsc, runc, OCI runtimes, seccomp, or checkpoint/restore systems. - Linux kernel development, virtualization, sandboxing, kernel modules, or device proxying. - CUDA, ROCm, GPU drivers, accelerator virtualization, or GPU profiling. - RDMA and high-performance networking. - FUSE, EROFS, direct I/O, mmap, page-cache behavior, or storage engines. - Large-memory or multi-GPU inference and training systems. - Contributions to open-source systems software. Prior gVisor or machine-learning experience is not required. We care more about strong systems fundamentals, curiosity, and the ability to learn unfamiliar parts of the stack. WHY THIS ROLE: The container runtime is directly on the critical path for inference performance. Improvements here can substantially reduce cold starts, increase token throughput, unlock new accelerator types, and make previously impractical workloads possible.This is an opportunity to work on unusually deep systems problems with immediate production impact. You’ll have room to shape the architecture, contribute to open-source runtime technology, and take ownership of foundational infrastructure used by every inference and training workload on Modal.

Location: Remote - US Workplace: Remote ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE TEAM: We are a small but mighty team of three analytics engineers powering LangChain’s internal data infrastructure and analytics. We’re a full-stack team, meaning we work end-to-end across the data stack, from data ingestion to enabling self-serve agentic analytics. Learn more about what we’ve built so far here https://www.langchain.com/blog/agent-data-stack! ABOUT THE ROLE: We are expanding our data team and looking for a analytics engineer to join us. We build products used by elite companies and over a million developers, and data plays a critical role in sharping our strategies and decision making. In this role you will help lay the foundation for business teams to diagnose issues, uncover opportunities, and drive success using data. If you enjoy building data infrastructure and empowering teams with actionable insights, this role is for you. *Location: SF, NYC, Boston, or Remote U.S. WHAT YOU WILL DO: - Build scaleable dbt models and context that describe our business, powering a self-serve analytics experience - Work with and expand on our foundational data stack — Fivetran, dbt, BigQuery, Hex - Connect data from a variety of sources (Salesforce, Stripe, Metronome, Postgres, etc) into our BigQuery warehouse - Build dashboards that track progress against company goals and KPIs - Analyze product usage and operational data to surface insights around customer health, adoption, and revenue - Develop and leverage a deep understanding of our business metrics to drive alignment and decision-making WHAT YOU'LL BRING: - 3+ years experience in a related role (analytics engineer, data engineer, or similar) - Technical proficiency in BigQuery, dbt, Hex, Fivetran, Segment (or similar tools) - Detail oriented, enjoys data spelunking, and can synthesize findings effectively - Curiosity and a strong business sense to help anticipate needs and generate meaningful insights - Start up DNA. You thrive in fast-paced and unstructured environments and are energized by finding out what matters most - You are self-directed - you don’t wait for process or oversight to start making an impact Compensation & Benefits: We offer competitive compensation that includes base salary, meaningful equity, and benefits such as health and dental coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation will vary based on role, level, and location. For team members in the EU and UK, we provide locally competitive benefits aligned with regional norms and regulations. Annual salary range: $140,000-$180,000 Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: San Francisco, CA Workplace: OnSite ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. About the team SmithDB is LangChain's internal database team. We're building a storage and query layer purpose-built for AI observability and evaluation. Within six months we went from idea to a production system that offers industry leading performance and scalability for agent observability data. We're a small, fast team of systems engineers tackling genuinely hard problems: storage layout, query execution, compaction, and scaling toward trillions of agent traces. We develop in Rust, run on Kubernetes, and integrate tightly with S3/GCS/Azure Blob. There are no legacy constraints; this is a greenfield system with real production load and ambitious engineering goals.   About the role We're looking for a hands-on Engineering Manager to lead the SmithDB team. This is not a pure people-management role. You'll write production code, review PRs at the systems level, make architectural calls, and be in the weeds alongside your engineers. At the same time, you'll own team health, hiring, technical roadmap, and coordination with the broader LangSmith platform. The ideal candidate has deep systems or database engineering experience and genuinely prefers to stay technical while growing a team.   What you'll do - Write and review production Rust code across ingestion, query execution, and storage layers - Lead architectural decisions on storage format, compaction, indexing, and query planning - Drive performance investigations using memory and CPU profiling tools; own the path from profiling to shipped fix - Design and harden the distributed deployment of SmithDB services on Kubernetes (multi-tenant, high-throughput, low-latency) - Contribute to cloud object store integrations (S3, GCS, Azure Blob) and set the standard for how SmithDB manages data at rest and in flight - Build and maintain observability for the engine itself: metrics, tracing, debug tooling - Manage a small but growing team of systems engineers: set goals, run 1:1s, provide technical mentorship, and grow careers - Own the SmithDB technical roadmap in partnership with LangSmith product and engineering leadership - Communicate progress, risks, and tradeoffs clearly to the broader organization: you write concise, decision-ready updates   What you'll bring - 7+ years in systems or database engineering, with at least 2 years in a technical lead or engineering management role - Production Rust experience — you can write it, review it, and have opinions on how to structure it at scale - Deep understanding of database or storage engine internals: query execution, storage layouts, indexing, compaction - Proficiency in systems performance analysis: memory allocators, CPU hotspots, lock contention, async runtimes (Tokio) - Experience deploying and operating distributed services on Kubernetes in a production, multi-tenant environment - Familiarity with cloud object storage (S3-compatible APIs, consistency models, cost/performance tradeoffs) - Proven track record of managing engineers — you can recruit, retain, and level-up a team without losing your technical edge Nice-to-have: - Experience building or contributing to columnar storage formats (Parquet, Arrow), OLAP query engines, or time-series stores - Background in observability infrastructure or tracing pipelines (OpenTelemetry, ClickHouse, Prometheus) - Experience scaling a system from early-stage to hundreds of billions / trillions of records   Compensation Salary Range: $240,000-$300,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: Remote, Global Workplace: Remote ABOUT SUPABASE Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth. About the Role We are looking for a Head of AI Native Operations to build the autonomous systems that run Supabase. Supabase is building an AI-native internal operating system, where agents carry the operational load end to end. We are standing up a new central team to build that platform and run it in production. This is the role that leads it, and it is hands-on. You design the architecture, build the first versions of the critical pieces, and are accountable for whether every agent we run is correct, safe, and improving over time. We build rather than buy, and there are no settled best practices for most of this yet, so you will be setting them. You will lead a team of senior individual contributors extending the platform and driving adoption across teams. What You’ll Be Responsible For In this role, you’ll: - Own the agent platform architecture: The harness and orchestration layer and connectors into company systems, shared context and memory, and the path from prototype to production. - Catch regressions before they ship: Model, prompt, and tool changes can’t ship until they pass the evals. When a new model comes out, you know within hours whether to adopt it. - Make every agent observable: Every run and every decision is traced. For any agent at any time, you can answer what it did, why, what it cost, and how its quality is trending. - Own safety and trust: Design the controls that let agents act without a human in the loop: least-privilege credentials, hard policy limits, escalation thresholds, audit logs, sandboxing, and prompt-injection defenses. - Replace workflows, don’t assist them: Pick the workflows agents can fully own today and take them to production. - Turn wins into a platform: Package what works into reusable components, templates, and eval harnesses so other teams can ship their own production agents without starting from scratch. - Build and direct the team: Hire and grow senior ICs, review their designs and pull requests, and hold the quality bar. - Measure what matters: Track workflows automated, eval pass rates, cost per run, and work absorbed against the hiring plan. How You’ll Think A Point of View on Where Automation Wins You have a thesis about how AI and automation change the way a company operates, and it comes from building, not reading. You can look at a business and say which workflows agents can own today, which they will own in 12 months as models improve, and which still need people, and why. You defend that view with evidence from systems you have shipped, and you update it when the evals tell you to. Eval-Driven You don’t trust an agent because the demo looked good. You trust it because it passes a test set of real cases, and you know which cases it fails. When anything changes, your first question is “what do the evals say?” Inversion Thinking Left alone, an autonomous system tends to fail quietly, or people route around it. So the first question about any agent isn’t “does it work on the happy path?” but “how will this break, and how will we know?” The design follows from that answer: what the agent is never allowed to do, what it escalates, and which alert fires when quality drifts. Recursive Thinking Every system you build should produce the evidence that grades it. An agent isn’t done when it works. It’s done when it tells you, without you in the loop, that it has stopped working. Must Have - Hands-on agent building: Have personally designed and built autonomous agent or LLM systems that ran in production and that others depended on. Prototypes, demos, and configuring a vendor tool don’t count. You don’t need to be a career software engineer, but you must have built these systems yourself. - Architecture depth: Can explain how the pieces fit together (orchestration, tool and data access, context and memory, tracing, evals, guardrails, deployment), with opinions on current frameworks. - Security judgment: Have shipped agents that take real actions with real permissions, and designed the controls that made that safe. - A tested point of view: Can argue, with examples from your own builds, where autonomous systems create real business leverage and where they don’t yet. - Technical leadership: Have led senior builders and set the quality bar through design and code review. Strong Signal - Have replaced a human-run business workflow (finance, operations, support, release management) end to end with an autonomous system. - Are native to Git, Markdown, and pull requests, and comfortable reading and writing Python or TypeScript. - Have taken an internal platform from zero to adoption by teams you did not control. - A software engineering background is a plus, but not required. What Success Looks Like - Six months: 20+ autonomous agents in production on the shared platform, each with an eval suite, tracing, and a named owner. - Regressions get caught, not discovered: Quality problems surface in an alert or dashboard before a user reports them. - Workflows replaced, not assisted: Multiple high-volume workflows are fully owned by agents, with humans handling only escalations. - Trusted by default: No agent causes material financial, security, or customer harm, and every agent’s permissions and actions can be audited. - Teams ship their own: At least three teams outside the core team run production agents built on the platform. - Autonomous team: Your two reports work independently, and you spend your time on architecture and review rather than execution. WHAT WE OFFER - Fully Remote We hire globally. We believe you can do your best work from anywhere. There are no Supabase offices, but we provide a WeWork membership or co-working allowance you can use anywhere in the world. - ESOP Every team member receives ESOP (equity ownership) in the company. We want everyone to share in the upside of what we’re building together. - Tech Allowance Use this budget to set up your ideal work environment—laptop, monitor, headphones, or whatever helps you do your best work. - Health Benefits Supabase covers 100% of health insurance for employees and 80% for dependents, wherever you are. Your wellbeing and your family’s health are important to us. - Annual Off-Sites Once a year, the entire company gathers in a new city for a week of connection, collaboration, and fun. It’s a highlight of our year. - Flexible Work We operate asynchronously and trust you to manage your own time. You know what needs to be done and when. - Professional Development Every team member receives an annual education allowance to spend on learning—courses, books, conferences, or anything that supports your growth. ABOUT THE TEAM Supabase was born-remote and open-source-first. We believe our globally distributed team is our secret weapon in building tools developers love. - ~400 team members - 60+ countries - 20+ languages spoken - Over $1B raised (including our $500M Series F) - 540,000+ community members We move fast, build in public, and use what we ship. If it’s in your project, we probably use it in ours too. We believe deeply in the open-source ecosystem and strive to support—not replace—existing tools and communities.

Location: San Francisco, CA Workplace: OnSite ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE ROLE We're hiring an IT Systems Administrator to join the founding IT team in San Francisco. You'll run most of our SaaS stack day to day, from maintenance and configuration changes to access and troubleshooting. You'll also build the automation that keeps that stack running as we grow. This is a role for someone who does a bit of everything: helping an employee that’s locked out, shipping a terraform change, and building an automation that removes a manual task. The ideal candidate has startup experience, is comfortable with ambiguity, and heavily leans into automation. WHAT YOU'LL DO SaaS Administration - Own the day-to-day administration of our SaaS stack, including maintenance, configuration changes, and license management - Administer LangSmith, our product, and use APIs to automate admin work - Administer identity and permissions across core SaaS platforms such as Google Workspace, Slack, GitHub, Zoom, and Microsoft 365 Automation and Tooling - Develop scripts, integrations, and reusable workflows using low or no code tools - Connect systems through APIs and event-driven workflows to reduce manual work Identity Management - Administer Okta and user access - Manage Okta group rules that help define our RBAC policy - Establish repeatable standards and automation for employee lifecycle, group management, application provisioning, and access reviews Client Platform Administration - Administer our MDM platform, Iru, to enforce policy configurations, patching, zero-touch deployment, and custom desktop environment configurations - Automate the hardware lifecycle from procurement, assignment, return, and recycling Core IT Operations - Provide hands-on troubleshooting and support to employees in the office and remotely across hardware, software, networking, and SaaS tools - Build and maintain the harness for our AI ITSM agent, including the tools, playbooks, and knowledge it needs to resolve issues on its own - Write documentation and playbooks, and use recurring support issues to guide what to automate next WHAT YOU'LL BRING - 3+ years of experience in IT systems administration or IT engineering, ideally at a fast-growing startup - Experience administering a broad SaaS stack that includes Google Workspace, Slack, Notion, and AI tools like Claude and ChatGPT - Hands-on experience administering Okta, including SSO, SCIM provisioning, and Okta Workflows - Comfort with REST APIs, webhooks, and API authentication methods - Experience using coding agents (e.g. Claude Code) as part of your day-to-day workflow - Experience with a macOS MDM platform and endpoint security tooling - Solid networking fundamentals (TCP/IP, DNS, DHCP, VPNs, wireless) - Clear communication, with patience for non-technical users - Annual salary range: $120,000-$160,00 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

The role You will build and lead our Forward Deployed Engineering team: the engineers who connect estaie to the hospitality ecosystem and make those integrations work in production. You own how the team works, what it ships, and the quality bar it holds.

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