Разработка вакансии

– Опыт коммерческой iOS-разработки от 3 лет. – Уверенное знание Swift, SwiftUI / UIKit.

— Разработка расчётных плагинов для NanoCAD. — Проектирование модульной архитектуры и математических моделей.

— Разработка и развитие AI-продуктов. — Работа с данными и современными технологиями.

Задачи: — Строить надежные backend-системы и проектировать современные API для новых функций продукта. — Работать в кросс-функциональной fullstack-команде в тесном сотрудничестве с продуктом, дизайном, customer success, поддержкой и продажами. — Работать напрямую с сооснователями компании. — Иметь большую автономию и влияние. — Выпускать новые функции каждую неделю. — Владеть центральными, сложными компонентами приложения. — Вести и реализовывать дорожную карту продукта, превращая черновые спецификации в функции. — Находить элегантные решения проблем удобства использования. — Обеспечивать лидерство и наставничество для других инженеров команды. — Реализовывать масштабируемый, стабильный и удобный продукт, способный справляться с текущим ростом. — Сотрудничать с опытными инженерами на этапах проектирования, разработки и поддержки продукта. Требования: — Опыт проектирования и поддержки сложных, больших и растущих систем. — При рассмотрении новых системных дизайнов или кода естественно учитывать возможные ошибки: крайние случаи, режимы отказа, узкие места, миграции, релизы, интересные метрики и т.д. — Любовь к отладке и поиску корневых причин проблем в продакшене. — Проактивность: при обнаружении проблем быстро исправлять или предлагать улучшения. — Стремление использовать лучшие практики и всегда тестировать поставляемое ПО. Условия: — Работа в стартапе после раунда Series A. — Поддержка Y Combinator. — Сильная техническая команда основателей из MIT и IST. — Быстрорастущий стартап с продуктом, имеющим рыночное соответствие. — Конкурентная зарплата. — Медицинская страховка. — Опционы на акции. — Ежегодная корпоративная поездка в секретное место и другие бонусы.

Position - Digital IC Design Engineer. Requirements - Bachelors degree in Electrical Engineering, Electronics Technology, Electrical Engineering Technology, Electrical and Computer Engineering or related field.

Location: Remote, Canada; Remote, United States GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Senior Backend Engineer on GitLab's Security Factory: Code Security team, you help developers find and fix security issues. Those issues live in the code they write and in the open source components they depend on. Your work spans complementary parts of a complete security analysis. On the dependency analysis side, you teach the analysis engine what a project depends on. You parse dependency manifests, lockfiles, and SBOMs so the engine knows which libraries and frameworks are in play and how the code uses them. You also extend the service that turns security advisories into automated merge requests that update vulnerable dependencies. On the vulnerability detection side, you grow GitLab's security analysis engine with hybrid analyzers that blend rule-based detection and AI reasoning. You build and apply the tooling that develops, evaluates, and ships those analyzers, and you measure how well they find real problems. That work also expands coverage of the libraries, frameworks, and AI agent tooling that real-world applications are built on. These threads reinforce each other. What a project depends on, and how its code uses those dependencies, are parts of one picture, and this team works across all of it. We make thoughtful use of AI-assisted development tools in our daily work. We expect you to use them effectively and with good judgment. What you do Act as the directly responsible individual (DRI) for team initiatives from design through delivery, shipping with minimal guidance in partnership with the technical lead Bring systems built by one engineer to team ownership through documentation, tests, and shared review Design and ship analyzers that pair deterministic analysis capabilities with AI-driven analysis, and build the evaluation harnesses that measure their false positives and missed findings against benchmark applications with known vulnerabilities, raising the bar for what counts as a trustworthy result. That includes detection rules mapped to CWE and the test fixtures that prove they work. Package those analyzers for every place GitLab runs them, including CI jobs, AI agent workflows, and command-line tools, with findings reported in GitLab's standard security report formats Design and ship the manifest, lockfile, and SBOM parsing that tells the static analysis engine what a project depends on, and extend it to new ecosystems and formats Ship features across the automated remediation service that turns security advisories into dependency update merge requests, from sandboxed updates to merge request creation Solve technical problems of high scope and complexity, actively seek out difficult impediments affecting the whole team, and advocate for improvements to quality, security, and performance with Product Management, Engineering stakeholders such as Frontend and UX, and partner teams such as Code Scanning and Composition Analysis Mentor Intermediate engineers through code review and pairing, and maintain our internal standards for style, maintainability, and best practices through review Participate in on-call rotations to assist troubleshooting product operations, security operations, and urgent engineering issues What you bring Experience building your own LLM tooling, such as a harness, an agent pipeline, or evaluations, with the judgment to know when output is trustworthy and when it isn't Substantial professional experience writing and testing production code in a systems language, particularly Go and/or Rust, with depth in at least one. We use both, plus Ruby on the remediation side and Python for some analyzers, and value willingness to work across them. Familiarity with package managers and dependency management in one or more language ecosystems, such as npm, Maven, pip, Bundler, or Cargo. Experience building tooling around them is better still. Demonstrated application security experience, such as vulnerability research, secure code review, or writing detection rules, and fluency with vulnerability classes (OWASP Top 10, CWE) and the software supply chain A track record of taking ownership of ambiguous problems and shipping with minimal guidance, with the self-motivation and organizational skills suited to a remote, largely asynchronous environment Demonstrated capacity to communicate clearly and concisely about technical problems, and to write design proposals that bring a team to a decision Helpful experience Experience evaluating AI-driven detection against labeled data, including measuring false positives and missed findings Experience with performance optimization at scale Hands-on program analysis experience, such as parsing, ASTs, or data-flow analysis Familiarity with popular web or mobile application frameworks and how they handle input, data, and configuration Experience with containerized workflows and CI/CD (we use Docker heavily) About the team The Security Factory: Code Security team builds GitLab's code-level security scanning capabilities, spanning static application security testing and dependency scanning. We help developers find and fix security issues in both the code they write and the open source components they depend on, as early as possible. We work closely with the Static Analysis team on GitLab's SAST engines, with Composition Analysis on the broader software supply chain, and with other groups across the Sec Section. We rely heavily on asynchronous work across time zones. Remote-Global The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity . Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. United States Salary Range $139,200 — $235,200 USD How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

Location: Remote, Canada; Remote, Israel; Remote, United Kingdom; Remote, United States GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Staff Backend Engineer on GitLab's Security Factory: Code Scanning team, you help developers find and fix security issues. Those issues live in the code they write, and you set the technical direction for the static analysis engine that finds them. Your work spans two complementary parts of a complete security analysis. On the engine side, you shape how the static analysis toolkit models a program: parsing source into intermediate representations, resolving symbols, building call graphs, and tracking tainted data across files and languages. You define the architecture and specifications the team builds against, and you delegate component specifications within them to engineers and to the AI agents that implement them. On the evaluation side, you build and apply tooling that tests, measures, and validates what the engine finds against benchmark applications with known vulnerabilities. What the engine can model and how we measure what it finds are parts of one picture. As a Staff engineer you hold that picture, shape the long-range technical goals of the team, and raise the bar for every engineer on it. We build the engine with AI agents that write and review code from written specifications, under human direction. We expect you to direct that work effectively and with good judgment, and to help the team do the same. What you do Act as the directly responsible individual (DRI) for the team's highest-scope initiatives from design through delivery, shipping large features with minimal guidance and shaping the long-range goals of the team Bring systems built by one engineer to team ownership through documentation, tests, and shared review Set the technical direction for the AI-assisted tooling that implements, reviews, and validates engine changes and findings, design the checks that decide whether an agent-written change or generated result is fit to merge, and measure detection quality against benchmark applications with known vulnerabilities, raising the bar for what counts as a trustworthy result. That includes static application security testing (SAST) rules mapped to CWE and OWASP, and the test fixtures that prove they work. Own the architecture of the program model (parsing, symbol resolution, intermediate representations, call graphs, and taint and data-flow analysis) and of the pipeline that turns source code into findings, and define how both extend to new languages and frameworks Solve technical problems of the highest scope and complexity, actively seek out difficult impediments affecting the whole team, and advocate for improvements to quality, security, and performance with Product Management, UX, and partner teams such as Code Security and Composition Analysis Mentor all engineers on the team through code review and pairing, remove blockers to their autonomy, and shepherd the definition and improvement of our internal standards through review Participate in on-call rotations to assist troubleshooting product operations, security operations, and urgent engineering issues Define the overarching architecture and specification documents for the engine, delegate component specifications within them, and drive their implementation by AI agents and engineers working independently through phased plans, small reviewable units of change, and specifications kept in lockstep with the code Build and maintain the harness, agent instructions, and agentic skills that keep agent-written code trustworthy, including separate coding and reviewing agents, rules and tests the coding agents cannot change, independent review panels of agents from different model providers, and performance, API, and dependency gates, with risky changes escalated to human review Stay current with research in program analysis and security, run AI-assisted research and spikes, and turn the findings into prototypes, proposals, and upstream contributions, including responsible disclosure of findings in open source projects What you bring Experience building your own LLM tooling, such as a harness, an agent pipeline, or evaluations, with the judgment to know when output is trustworthy and when it isn't Extensive professional experience writing, testing, and reviewing production code in Rust, Go, or a comparable systems language, with depth in at least one. The engine is Rust, the analyzer wrapper is Go, and the monolith integration is Ruby, and we value willingness to work across them. Experience with performance optimization and with containerized workflows and CI/CD (we use Docker heavily) A deep program analysis and static analysis background, such as parsing and ASTs, intermediate representations (SSA, control-flow and call graphs), taint and data-flow analysis, type inference, incremental and fixpoint computation, or writing detection rules, with the ability to read, evaluate, and apply the research literature Deep application security experience, such as vulnerability research, secure code review, or writing detection rules, and fluency with vulnerability classes (OWASP Top 10, CWE) Demonstrated capacity to communicate clearly and concisely about complex technical, architectural, and organizational problems, and to write architecture and design specifications that bring a team to a decision A track record of taking ownership of ambiguous, team-wide problems and shipping them from concept to production with minimal guidance, with specific, regular async updates on progress, blockers, risks, and next steps Experience defining a system's overarching architecture, delegating component specifications to engineers and AI agents, and getting them implemented reliably A track record of mentoring engineers, raising a team's technical bar, and influencing technical direction by achieving consensus with peers and leadership Helpful experience Familiarity with popular web or mobile application frameworks and how they handle input, data, and configuration Experience designing guardrails for agent-written code, such as mutation testing, fuzzing, and CI gates the coding agent cannot modify A record of engaging with the research community, such as publications, tool papers, or upstream open source contributions in program analysis or security About the team The Security Factory: Code Scanning team develops GitLab's SAST capabilities for customer software repositories. We work closely with the Code Security team on scanning rules & flows, with Composition Analysis on the broader software supply chain, and with other groups across the Sec Section. We rely heavily on asynchronous work across time zones. Remote-Global The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity . Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. United States Salary Range $152,800 — $259,200 USD How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

About the job: QV.AC is a general purpose AI assistant that runs locally on your devices, giving people real control over their data and AI usage without cloud dependency or data harvesting. The focus is on local, on-device, privacy-preserving AI connected across Tether's peer-to-peer ecosystem. Responsibilities: Engineering: — Run the app and feature teams day to day: unblocking, reviewing, and keeping them shipping. — Set and hold a high engineering bar for performance, reliability, and clean APIs. — Own the technical design of features and the API surface between the AI core and the app. — Ensure close collaboration with AI research and deep tech teams on code reviews, design, and anything involving models or inference. Product Partnership: — Work alongside product managers to turn vision and roadmap into scoped, buildable work. — Push back when scope and reality don't match and propose better paths. — Bring an engineering perspective to product decisions, especially regarding local AI model capabilities and limitations. — Help the team move fast using AI tools and quick prototypes to validate ideas before commitment. Leadership: — Create clarity around team goals and define success. — Mentor team leads to build strong operating systems, improve collaboration, and grow as leaders. — Lead by example: actively contribute when needed and step back when teams are ready to own their work. Mandatory Requirements: — Experience managing engineers or engineering leads who ship consumer products, ideally AI-powered apps. — Strong product sense to distinguish good features from busywork. — Intuition for applied AI and on-device constraints such as model size, latency, memory, battery, and the gap between demos and reliable features. — Heavy use of AI tools in own work and enthusiasm for experimenting with new models and capabilities. — Deep knowledge of JavaScript and React. — Initiative, curiosity, resilience, and ability to give and receive direct critique. Preferred: — Experience with local or on-device inference, LLM evaluations, cross-platform mobile and desktop apps, or open source. Work format: — Remote work from anywhere in the world. Additional information: — Recruitment scams warning and official application channels provided. — Official careers page: https://tether.recruitee.com/ — Communication only via official company emails ending with @tether.to or @tether.io. — No requests for payment or financial details during hiring. — Candidates encouraged to mention the word EXTOLL when applying to confirm they read the job post fully.

Location: Atlanta, GA; Austin, TX; Dallas, TX; Las Vegas, NV; Nashville, TN; Seattle, WA; Boston, MA; Detroit, MI; San Diego, CA; Denver, CO 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 ROLE We're looking for a Deployed Engineer to join our Professional Services team, working directly with enterprise customers to build reliable, production agents. You'll translate vague enterprise workflows into concrete software specs and guide engineering teams through the resulting solution, or build it for them. You might spend a week designing a customer's agent architecture, a few weeks co-building their evaluation pipeline, or a quarter embedded inside their team shipping alongside their engineers. You are someone who's built real AI systems for production and can defend the technical tradeoffs within them. KEY RESPONSIBILITIES - Advising: Agent architecture design, evaluation strategy review, and best-practice production guidance. - Building: Co-build with the customer's engineering team across the full Agent Development Lifecycle (ADLC) in outcome-scoped engagements. - Embedding: Serve as a deployed engineer inside the customer's team for extended engagements, operating as a de facto member of their org to ship agent systems directly. - Agent Engineering: ADLC end-to-end, architecture design, orchestration patterns, evals, custom conversational UIs, and production deployment. - Applied AI: Post-training, supervised fine-tuning, harness engineering, trace mining, model selection and evaluation methodology. REQUIREMENTS - 4+ years of software engineering experience with deep expertise in Python. TypeScript/JavaScript a plus. - 2+ years of hands-on experience building and shipping production agent systems. - Strong client-facing communication skills, with the ability to confidently articulate architectural decisions to technical stakeholders (engineers, architects, CTOs). - Strong experience with LangChain/LangGraph/Deep Agents or comparable frameworks, including multi-agent patterns and state management (short and long-term memory). - Deep familiarity designing and implementing evaluation methodologies for non-deterministic AI systems. - Comfortable operating across the full spectrum from advisory to embedded delivery. - Willing to travel up to 20% of the time. NICE TO HAVE - Exposure to dataset curation and post-training techniques (SFT, DPO, RLHF) on open-weight models using tools like Axolotl, Unsloth, Hugging Face transformers, or TRL. - Experience with trace mining to drive continuous improvement loops LOCATION Remote COMPENSATION $150,000-$270,000 base + equity Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. 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: New York, NY Workplace: Hybrid 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 looking for a Deployed Engineer to join our Professional Services team, working directly with enterprise customers to build reliable, production agents. You'll translate vague enterprise workflows into concrete software specs and guide engineering teams through the resulting solution, or build it for them. You might spend a week designing a customer's agent architecture, a few weeks co-building their evaluation pipeline, or a quarter embedded inside their team shipping alongside their engineers. You are someone who's built real AI systems for production and can defend the technical tradeoffs within them. KEY RESPONSIBILITIES - Advising: Agent architecture design, evaluation strategy review, and best-practice production guidance. - Building: Co-build with the customer's engineering team across the full Agent Development Lifecycle (ADLC) in outcome-scoped engagements. - Embedding: Serve as a deployed engineer inside the customer's team for extended engagements, operating as a de facto member of their org to ship agent systems directly. - Agent Engineering: ADLC end-to-end, architecture design, orchestration patterns, evals, custom conversational UIs, and production deployment. - Applied AI: Post-training, supervised fine-tuning, harness engineering, trace mining, model selection and evaluation methodology. REQUIREMENTS - 4+ years of software engineering experience with deep expertise in Python. TypeScript/JavaScript a plus. - 2+ years of hands-on experience building and shipping production agent systems. - Strong client-facing communication skills, with the ability to confidently articulate architectural decisions to technical stakeholders (engineers, architects, CTOs). - Strong experience with LangChain/LangGraph/Deep Agents or comparable frameworks, including multi-agent patterns and state management (short and long-term memory). - Deep familiarity designing and implementing evaluation methodologies for non-deterministic AI systems. - Comfortable operating across the full spectrum from advisory to embedded delivery. - Willing to travel up to 20% of the time. NICE TO HAVE - Exposure to dataset curation and post-training techniques (SFT, DPO, RLHF) on open-weight models using tools like Axolotl, Unsloth, Hugging Face transformers, or TRL. - Experience with trace mining to drive continuous improvement loops LOCATION New York, New York COMPENSATION $150,000-$300,000 base + equity Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. 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: New York, NY 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 looking for a Deployed Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems. This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains. This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture. KEY RESPONSIBILITIES - Infrastructure & Platform Engineering: Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelines - Agent Engineering & Development: Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operations - Customer Engagement & Assessment: Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teams WHAT WE'RE LOOKING FOR REQUIRED EXPERIENCE 7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to apply Infrastructure & Platform: - 3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure) - Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deployments - Experience with Infrastructure as Code (Terraform, Helm) and GitOps practices - Knowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizing - Experience designing high-availability and disaster recovery solutions - Strong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog) - Experience with CI/CD pipelines for infrastructure and applications Agent Engineering & Development: - 1+ years of experience building production AI/ML applications or agents - Strong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applications - Experience with state management patterns (short-term and long-term memory) - Experience designing and implementing evaluation frameworks for AI applications - Strong prompt engineering skills with experience in optimization and A/B testing - Experience with vector stores, RAG patterns, and knowledge organization - Experience with tool integration, API design, and error handling patterns - Strong Python and/or TypeScript development skills Customer-Facing: - Customer-facing experience with enterprise customers - Experience conducting technical assessments or infrastructure audits - Strong communication skills with ability to explain technical concepts to diverse audiences KEY ATTRIBUTES - Strong problem-solving skills with ability to analyze complex requirements and design elegant solutions - Excellent customer-facing communication skills, able to explain technical concepts to diverse audiences - Experience working cross-functionally with engineering teams, product teams, and customers - Consultative approach with ability to understand customer needs, provide recommendations, and guide implementation - Ability to balance infrastructure architecture with agent development work - Strong engineering background with hands-on development experience - Willing to travel up to 20% of the time Location: New York City Compensation: $170,000-$300,000 base salary + equity Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. 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: Austin, TX 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 ROLE We're looking for a Deployed Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems. This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains. This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture. KEY RESPONSIBILITIES - Infrastructure & Platform Engineering: Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelines - Agent Engineering & Development: Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operations - Customer Engagement & Assessment: Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teams WHAT WE'RE LOOKING FOR REQUIRED EXPERIENCE 7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to apply Infrastructure & Platform: - 3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure) - Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deployments - Experience with Infrastructure as Code (Terraform, Helm) and GitOps practices - Knowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizing - Experience designing high-availability and disaster recovery solutions - Strong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog) - Experience with CI/CD pipelines for infrastructure and applications Agent Engineering & Development: - 1+ years of experience building production AI/ML applications or agents - Strong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applications - Experience with state management patterns (short-term and long-term memory) - Experience designing and implementing evaluation frameworks for AI applications - Strong prompt engineering skills with experience in optimization and A/B testing - Experience with vector stores, RAG patterns, and knowledge organization - Experience with tool integration, API design, and error handling patterns - Strong Python and/or TypeScript development skills Customer-Facing: - Customer-facing experience with enterprise customers - Experience conducting technical assessments or infrastructure audits - Strong communication skills with ability to explain technical concepts to diverse audiences KEY ATTRIBUTES - Strong problem-solving skills with ability to analyze complex requirements and design elegant solutions - Excellent customer-facing communication skills, able to explain technical concepts to diverse audiences - Experience working cross-functionally with engineering teams, product teams, and customers - Consultative approach with ability to understand customer needs, provide recommendations, and guide implementation - Ability to balance infrastructure architecture with agent development work - Strong engineering background with hands-on development experience - Willing to travel up to 20% of the time Location: Austin, Texas Compensation: $170,000-$270,000 base salary + equity Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. 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: Dallas, TX 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 ROLE We're looking for a Deployed Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems. This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains. This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture. KEY RESPONSIBILITIES - Infrastructure & Platform Engineering: Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelines - Agent Engineering & Development: Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operations - Customer Engagement & Assessment: Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teams WHAT WE'RE LOOKING FOR REQUIRED EXPERIENCE 7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to apply Infrastructure & Platform: - 3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure) - Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deployments - Experience with Infrastructure as Code (Terraform, Helm) and GitOps practices - Knowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizing - Experience designing high-availability and disaster recovery solutions - Strong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog) - Experience with CI/CD pipelines for infrastructure and applications Agent Engineering & Development: - 1+ years of experience building production AI/ML applications or agents - Strong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applications - Experience with state management patterns (short-term and long-term memory) - Experience designing and implementing evaluation frameworks for AI applications - Strong prompt engineering skills with experience in optimization and A/B testing - Experience with vector stores, RAG patterns, and knowledge organization - Experience with tool integration, API design, and error handling patterns - Strong Python and/or TypeScript development skills Customer-Facing: - Customer-facing experience with enterprise customers - Experience conducting technical assessments or infrastructure audits - Strong communication skills with ability to explain technical concepts to diverse audiences KEY ATTRIBUTES - Strong problem-solving skills with ability to analyze complex requirements and design elegant solutions - Excellent customer-facing communication skills, able to explain technical concepts to diverse audiences - Experience working cross-functionally with engineering teams, product teams, and customers - Consultative approach with ability to understand customer needs, provide recommendations, and guide implementation - Ability to balance infrastructure architecture with agent development work - Strong engineering background with hands-on development experience - Willing to travel up to 20% of the time Location: Dallas, TX Compensation: $170,000-$270,000 base salary + equity Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. 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: Los Angeles, CA; Salt Lake City, UT; Seattle, WA; Denver, CO 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 ROLE We're looking for a Deployed Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems. This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains. This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture. KEY RESPONSIBILITIES - Infrastructure & Platform Engineering: Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelines - Agent Engineering & Development: Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operations - Customer Engagement & Assessment: Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teams WHAT WE'RE LOOKING FOR REQUIRED EXPERIENCE 7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to apply Infrastructure & Platform: - 3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure) - Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deployments - Experience with Infrastructure as Code (Terraform, Helm) and GitOps practices - Knowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizing - Experience designing high-availability and disaster recovery solutions - Strong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog) - Experience with CI/CD pipelines for infrastructure and applications Agent Engineering & Development: - 1+ years of experience building production AI/ML applications or agents - Strong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applications - Experience with state management patterns (short-term and long-term memory) - Experience designing and implementing evaluation frameworks for AI applications - Strong prompt engineering skills with experience in optimization and A/B testing - Experience with vector stores, RAG patterns, and knowledge organization - Experience with tool integration, API design, and error handling patterns - Strong Python and/or TypeScript development skills Customer-Facing: - Customer-facing experience with enterprise customers - Experience conducting technical assessments or infrastructure audits - Strong communication skills with ability to explain technical concepts to diverse audiences KEY ATTRIBUTES - Strong problem-solving skills with ability to analyze complex requirements and design elegant solutions - Excellent customer-facing communication skills, able to explain technical concepts to diverse audiences - Experience working cross-functionally with engineering teams, product teams, and customers - Consultative approach with ability to understand customer needs, provide recommendations, and guide implementation - Ability to balance infrastructure architecture with agent development work - Strong engineering background with hands-on development experience - Willing to travel up to 20% of the time Location: Remote Compensation: $170,000-$270,000 base salary + equity Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. 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 ROLE We're looking for a Deployed Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems. This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains. This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture. KEY RESPONSIBILITIES - Infrastructure & Platform Engineering: Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelines - Agent Engineering & Development: Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operations - Customer Engagement & Assessment: Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teams WHAT WE'RE LOOKING FOR REQUIRED EXPERIENCE 7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to apply Infrastructure & Platform: - 3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure) - Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deployments - Experience with Infrastructure as Code (Terraform, Helm) and GitOps practices - Knowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizing - Experience designing high-availability and disaster recovery solutions - Strong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog) - Experience with CI/CD pipelines for infrastructure and applications Agent Engineering & Development: - 1+ years of experience building production AI/ML applications or agents - Strong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applications - Experience with state management patterns (short-term and long-term memory) - Experience designing and implementing evaluation frameworks for AI applications - Strong prompt engineering skills with experience in optimization and A/B testing - Experience with vector stores, RAG patterns, and knowledge organization - Experience with tool integration, API design, and error handling patterns - Strong Python and/or TypeScript development skills Customer-Facing: - Customer-facing experience with enterprise customers - Experience conducting technical assessments or infrastructure audits - Strong communication skills with ability to explain technical concepts to diverse audiences KEY ATTRIBUTES - Strong problem-solving skills with ability to analyze complex requirements and design elegant solutions - Excellent customer-facing communication skills, able to explain technical concepts to diverse audiences - Experience working cross-functionally with engineering teams, product teams, and customers - Consultative approach with ability to understand customer needs, provide recommendations, and guide implementation - Ability to balance infrastructure architecture with agent development work - Strong engineering background with hands-on development experience - Willing to travel up to 20% of the time Location: San Francisco Compensation: $170,000-$300,000 base salary + equity Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. 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: Toronto, Ontario, Canada Workplace: Hybrid ABOUT SENTRY Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. ABOUT THE TEAM The Billing team sits at the intersection of product, finance, and infrastructure. They're responsible for ensuring every observable event—errors, logs, traces, tokens—gets accurately measured, priced, and billed. Their work directly impacts company revenue and customer trust, requiring distributed systems expertise, attention to financial accuracy, and deep understanding of product usage patterns. The team works cross-functionally with product, engineering, BizOps, marketing, and sales to build systems that enable new products and pricing models. ABOUT THE ROLE As a Senior Software Engineer, you will architect and scale the core systems that power Sentry's billing infrastructure, ensuring accuracy and reliability at massive scale.   - You will collaborate on building the next generation of Sentry’s usage tracking pipeline, processing hundreds of billions of events daily with low latency and financial-grade accuracy. - You will help design flexible pricing primitives that support everything from per-event usage billing to complex enterprise contracts, enabling product and sales teams to experiment rapidly while maintaining revenue accuracy and reduced time-to-market for new products. - You will contribute to technical decisions on data consistency challenges unique to billing—like handling event delays, retroactive pricing changes, and distributed count reconciliation across our infrastructure. YOU'LL LOVE THIS JOB IF YOU - Want to solve the "easy to explain, hard to build" problems—like ensuring a customer's bill matches their usage perfectly, even when processing hundreds of billions of events daily across distributed systems. - Thrive on constraints that force elegant design: financial accuracy is non-negotiable, customer trust depends on billing transparency, and the system must scale with Sentry's user and product growth without rearchitecting every year. - Enjoy partnering across the organization—from BizOps and sales to marketing and leadership—where your code directly impacts ARR and your architectural decisions show up in board-level metrics. TO THRIVE IN THIS ROLE, YOU HAVE - Built or significantly improved systems with high-stakes accuracy requirements. - Mentored engineers through ambiguous, high-stakes projects. - Operated services where reliability includes uptime and also financial correctness. The base salary range (or hourly wage range, if applicable) that Sentry reasonably expects to pay for this position is $227,000 to $420,000 CAD. A successful candidate’s actual base salary (or hourly wage) amount will be determined by a variety of relevant factors including, without limitation, the candidate’s work location, education, work and other relevant experience, skills, and job-related knowledge. A successful candidate will be eligible to participate in Sentry’s employee benefit plans/programs applicable to the candidate’s position (including incentive compensation, equity grants, paid time off, and group health insurance coverage). See Sentry Benefits https://sentry.io/careers/ for more details about the Company’s benefit plans/programs.   EQUAL OPPORTUNITY AT SENTRY Sentry is committed to providing equal employment opportunities to its employees and candidates for employment regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, or other legally-protected characteristic. This commitment includes the provision of reasonable accommodations to employees and candidates for employment with physical or mental disabilities who require such accommodations in order to (a) perform the essential functions of their jobs, or (b) seek employment with Sentry. We strive to build a diverse team, with an inclusive culture where every teammate can thrive. Sentry is an open-source company because we believe that everyone, everywhere, should have the ability and tools to make great software. Software should be accessible. That starts with making our industry accessible. If you need assistance or an accommodation due to a disability, you may contact us at accommodations@sentry.io. Want to learn more about how Sentry handles applicant data? Get the details in our Applicant Privacy Policy https://sentry.io/careers/applicantprivacy/.

Location: San Francisco, California Workplace: Hybrid ABOUT SENTRY Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. ABOUT THE TEAM The Billing team sits at the intersection of product, finance, and infrastructure. They're responsible for ensuring every observable event—errors, logs, traces, tokens—gets accurately measured, priced, and billed. Their work directly impacts company revenue and customer trust, requiring distributed systems expertise, attention to financial accuracy, and deep understanding of product usage patterns. The team works cross-functionally with product, engineering, BizOps, marketing, and sales to build systems that enable new products and pricing models. ABOUT THE ROLE As a Senior Software Engineer, you will architect and scale the core systems that power Sentry's billing infrastructure, ensuring accuracy and reliability at massive scale.   - You will collaborate on building the next generation of Sentry’s usage tracking pipeline, processing hundreds of billions of events daily with low latency and financial-grade accuracy. - You will help design flexible pricing primitives that support everything from per-event usage billing to complex enterprise contracts, enabling product and sales teams to experiment rapidly while maintaining revenue accuracy and reduced time-to-market for new products. - You will contribute to technical decisions on data consistency challenges unique to billing—like handling event delays, retroactive pricing changes, and distributed count reconciliation across our infrastructure. YOU'LL LOVE THIS JOB IF YOU - Want to solve the "easy to explain, hard to build" problems—like ensuring a customer's bill matches their usage perfectly, even when processing hundreds of billions of events daily across distributed systems. - Thrive on constraints that force elegant design: financial accuracy is non-negotiable, customer trust depends on billing transparency, and the system must scale with Sentry's user and product growth without rearchitecting every year. - Enjoy partnering across the organization—from BizOps and sales to marketing and leadership—where your code directly impacts ARR and your architectural decisions show up in board-level metrics. TO THRIVE IN THIS ROLE, YOU HAVE - Built or significantly improved systems with high-stakes accuracy requirements. - Mentored engineers through ambiguous, high-stakes projects. - Operated services where reliability includes uptime and also financial correctness. The base salary range (or hourly wage range, if applicable) that Sentry reasonably expects to pay for this position is $215,000 to $400,000. A successful candidate’s actual base salary (or hourly wage) amount will be determined by a variety of relevant factors including, without limitation, the candidate’s work location, education, work and other relevant experience, skills, and job-related knowledge. A successful candidate will be eligible to participate in Sentry’s employee benefit plans/programs applicable to the candidate’s position (including incentive compensation, equity grants, paid time off, and group health insurance coverage). See Sentry Benefits https://sentry.io/careers/ for more details about the Company’s benefit plans/programs.   EQUAL OPPORTUNITY AT SENTRY Sentry is committed to providing equal employment opportunities to its employees and candidates for employment regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, or other legally-protected characteristic. This commitment includes the provision of reasonable accommodations to employees and candidates for employment with physical or mental disabilities who require such accommodations in order to (a) perform the essential functions of their jobs, or (b) seek employment with Sentry. We strive to build a diverse team, with an inclusive culture where every teammate can thrive. Sentry is an open-source company because we believe that everyone, everywhere, should have the ability and tools to make great software. Software should be accessible. That starts with making our industry accessible. If you need assistance or an accommodation due to a disability, you may contact us at accommodations@sentry.io. Want to learn more about how Sentry handles applicant data? Get the details in our Applicant Privacy Policy https://sentry.io/careers/applicantprivacy/.

Location: San Francisco, California Workplace: Hybrid ABOUT SENTRY Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. ABOUT THE TEAM The Billing team sits at the intersection of product, finance, and infrastructure. They're responsible for ensuring every observable event—errors, logs, traces, tokens—gets accurately measured, priced, and billed. Their work directly impacts company revenue and customer trust, requiring distributed systems expertise, attention to financial accuracy, and deep understanding of product usage patterns. The team works cross-functionally with product, engineering, BizOps, marketing, and sales to build systems that enable new products and pricing models. As an Engineering Manager, you’ll lead a team of engineers owning critical workflows such as checkout and invoicing, while also developing new features to help customers manage their spend growth. In this role, you’ll partner across the organization to ensure our customers redeem everything Sentry has to offer and budget for future expansion. IN THIS ROLE YOU WILL - Strategic Planning & Roadmap: Define and drive the team's roadmap. Align team goals with organizational objectives and contribute to the overall platform strategy. - Technical Guidance & Operational Excellence: Provide technical leadership and guidance on complex distributed systems and design. Ensure the team is proactively identifying areas for improvement. - Cross-functional Collaboration: Partner closely with business and technical teams to translate business goals into actionable objectives and scalable solutions. - Team Leadership & Development: Lead, mentor, and grow a team of talented engineers, including Staff-level engineers. Build a culture of technical excellence, collaboration, continuous learning, and innovation within the team. - Communication & Reporting: Effectively communicate team progress, challenges, and strategic direction to senior leadership, stakeholders, and the wider organization. Represent the team's work internally and externally, including through blog posts and presentations. YOU’LL LOVE THIS JOB IF YOU - Are a product and platform-minded leader who enjoys distributed systems and software architecture problems. You regard Product and Design as your peers, seeking collaboration when determining product outcomes and technical priorities for the team. You’re comfortable managing delivery and shaping direction. - Have high agency and like to own your outcomes, including defining where Billing needs to be in 6 - 12 months, and translating that into team bets and priorities. - Enjoy leveraging your technical background to inform and validate the team’s decisions. - Thrive in cross-functional environments, collaborating with individuals across many disciplines to deliver the best solutions. - Love to foster career growth, finding opportunities for team members to stretch and excel. QUALIFICATIONS - Experience working on a customer-facing product, ideally within developer tools or high-traffic product surfaces. - Experience owning a product area end-to-end, from shipping new features through long-term maintenance and iteration. - Excellent communication skills and an ability to articulate technical concepts and tradeoffs clearly and succinctly. - Experience with scoping work, performing resource allocation, and establishing engineering milestones and delivery dates. - 5+ years professional engineering experience, preferably with Python, JavaScript/TypeScript or similar. - 2+ years of engineering management experience. The base salary range (or hourly wage range, if applicable) that Sentry reasonably expects to pay for this position is $240,000 to $450,000. A successful candidate’s actual base salary (or hourly wage) amount will be determined by a variety of relevant factors including, without limitation, the candidate’s work location, education, work and other relevant experience, skills, and job-related knowledge. A successful candidate will be eligible to participate in Sentry’s employee benefit plans/programs applicable to the candidate’s position (including incentive compensation, equity grants, paid time off, and group health insurance coverage). See Sentry Benefits https://sentry.io/careers/ for more details about the Company’s benefit plans/programs. EQUAL OPPORTUNITY AT SENTRY Sentry is committed to providing equal employment opportunities to its employees and candidates for employment regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, or other legally-protected characteristic. This commitment includes the provision of reasonable accommodations to employees and candidates for employment with physical or mental disabilities who require such accommodations in order to (a) perform the essential functions of their jobs, or (b) seek employment with Sentry. We strive to build a diverse team, with an inclusive culture where every teammate can thrive. Sentry is an open-source company because we believe that everyone, everywhere, should have the ability and tools to make great software. Software should be accessible. That starts with making our industry accessible. If you need assistance or an accommodation due to a disability, you may contact us at accommodations@sentry.io. Want to learn more about how Sentry handles applicant data? Get the details in our Applicant Privacy Policy https://sentry.io/careers/applicantprivacy/.