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Location: Toronto, Ontario Workplace: Hybrid Artificial Intelligence. Actual Impact. At Docebo, we’re using AI to change how people learn at work—and we mean actually change it. We’re an AI-powered learning platform that helps organizations create, deliver, and manage training all in one place. But our real mission goes deeper: we help teams move faster, work smarter, and focus on the work that truly matters. Our platform is built with intelligent, time-saving tools that personalize learning, eliminate busywork, and turn training from a checkbox into a superpower. The result? Better experiences for learners and real results for businesses. We’re shaping the future of learning with a team that isn’t afraid to challenge the status quo. If you're excited by the idea of using AI to make work-life better for real people–you’ll feel right at home here. And it’s not just what we build, it’s how we show up. At Docebo, our values aren’t just posters on the wall—they guide how we work every day. We call it the Docebo Heart: trust by default, assume positive intent, and create space for different perspectives to thrive. So… what are you waiting for? Join 900+ Docebians around the world and help us reinvent the way people learn, because learning never stops. 🚀 THE ADVENTURE AHEAD Our Salesforce org is the system of record for how Docebo sells, renews and serves customers. It carries CPQ, document generation, e-signature, provisioning and billing integrations, and a growing set of AI-driven workflows. The team that runs it is small, senior, and split between Canada and Italy. We've spent this year putting real structure behind it: a formal development lifecycle, a definition of ready for every ticket, a security standard for integrations, and a hardening program that is cleaning up years of accumulated access. We're adding a senior developer to carry that forward. You'll build on the platform every week, but you'll also be one of the people the rest of the team turns to when a design needs a second opinion, a connected app needs scrutiny, or a request needs someone to say "not like that, and here's why." ⚡ THE DAY-TO-DAY - Design and build. Deliver production-quality solutions in Apex, Lightning Web Components, Flow and platform configuration, from a clear problem statement through solution design, build, test and release. You'll work the full lifecycle, not just the ticket in front of you. - Integration security and governance. Review every new or changed integration against our integration security standard: connected app scopes, OAuth and token lifecycle, dedicated Okta-provisioned integration users, least-privilege permission sets. You'll push back on anything that asks for more access than it needs and document the decision. - Code and design review. Act as a reviewer for the team's pull requests and solution designs. Hold the line on maintainability, test coverage, deployment readiness and SOX-relevant change controls, and give feedback people can act on. - Platform health. Own a share of the technical-debt and hardening backlog: retiring unused automation, consolidating permission models, cleaning up legacy packages and integration users, and reducing the org's risk surface one deliberate change at a time. - Access and provisioning backstop. Be a point person for user activation, license allocation and permission assignment, and help move that work from manual cloning toward documented roles and automation. - Delivery partnership. Work directly with Revenue Operations, Finance, Marketing and Customer Success on scoping, and with the team's administrators and QA partner on testing and release. Take part in the daily check-in and the biweekly backlog and capacity review. - AI in the day-to-day. Use AI tooling to move faster on triage, documentation and build, and apply the judgment to validate what it produces before it ships. We care about both halves. 🌟 YOUR SUPERPOWERS - Deep hands-on Salesforce development. Several years shipping Apex, Lightning Web Components, Flow and integrations (REST, platform events, middleware) in a production org with real users and real release discipline. - A security mindset. You understand connected apps, OAuth scopes, permission sets, profiles and integration users well enough to spot a risky configuration and explain the fix. You treat "valid until revoked" as a problem, not a default. - Review experience. You've reviewed other engineers' code and designs and know how to be direct and useful at the same time. - Comfort in a governed environment. SOX controls, structured deployment windows, mandatory UAT, a source-control-backed deployment pipeline (we use Gearset and GitLab). - Clear communication, written and spoken, with technical and non-technical stakeholders. You can explain a trade-off to a VP and a defect to a developer. - Independence and judgment. You scope your own work, ask for clarity early, and don't wait to be told that a request is under-specified. - Working hours that overlap the team. Our daily check-in runs at 09:30 Eastern / 15:30 Central European; you'll need to be reliably available for it from either location. 🎯 BONUS POINTS - Salesforce Platform Developer II, Application Architect or Integration Architect certification. - Experience with Salesforce CPQ or Revenue Cloud, Conga or similar document generation, DocuSign, or a billing migration (we're moving billing to NetSuite). - Experience with Slack, Okta, Fivetran or Datadog as they relate to a Salesforce org. - Exposure to Data Cloud or Agentforce. - Italian language skills, or prior experience on a team split across North American and European time zones.   OUR HYBRID WORK PHILOSOPHY 🤝 Great work can happen anywhere but coming together helps us go further. Our team spends three days a week in the office (Tuesday-Thursday) to collaborate, solve problems, and learn from each other. With flexibility the rest of the week, it’s a balance designed to help everyone do their best work and keep growing. OUR TOTAL REWARDS PHILOSOPHY 🎉 Our Total Rewards Philosophy centers around three core areas to reward and care for our People: - Rewarding Impact: We lead with competitive pay to reward the impact, skills and traits that fuel our success. - Fostering Holistic Wellbeing: We care deeply about and invest in the whole person with programs that support our people’s physical, mental, and financial well-being. - Empowering Our Talent Culture: We build a culture of trust and empowerment by designing our rewards and benefits with transparency, equity, and flexibility, enabling our people to do their best work and stay for the long haul. OUR PROMISE TO YOU 😍 - Financial Wellness: Own a piece of Docebo through our Employee Share Purchase Plan (ESPP) at a 15% discount, plus a competitive compensation package. - Your Well-Being, Covered: You’ll get access to health benefits, so you can get the care you need when you need it. - Rest, Relax, Repeat: Rest and recharge with paid vacation days, two company-wide Docebo Days, floating holidays for cultural celebrations, and your birthday off! - Family First: We provide coverage offering you time with your little one(s) so you can soak up all those precious moments. Fun fact: we had 30 Docebian babies join the family in 2025! - Connections That Count: Connect with global communities through our Employee Resource Groups (including PRIDE, DWA, BIDOC, and Green Ambassadors) and company-wide events that keep the fun rolling all year long. ABOUT DOCEBO 💙 At Docebo, we create seamless, AI-powered learning experiences for over 3,000 customers worldwide. We have successfully achieved two IPOs (TSX: DCBO & NASDAQ: DCBO https://www.docebo.inc/home/default.aspx), been recognized as a top SaaS e-learning solution, and are growing exponentially in the process. We're a global company, with office across North America, EMEA, APAC, and beyond. Our team is guided by five core values—Grow Together Win Together, Build with Our Customer, Clear is Kind, Own Outcomes, Progress Over Perfection—that shape everything we do. If this resonates with you, now is the perfect time to join one of the fastest-growing learning technology companies in the world. Docebo is an Equal Employment Opportunity employer https://www.eeoc.gov/sites/default/files/2022-10/EEOC_KnowYourRights_screen_reader_10_20.pdf. We are committed to diversity and inclusion in our workforce. All qualified applicants and employees will receive consideration for employment regardless of their race, colour, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, citizenship status, age, disability, genetic information, or any other category protected under applicable law. As a federal contractor, Docebo is committed to the principles of affirmative action and equal employment opportunity for protected veterans and individuals with disabilities. Docebo does not discriminate because of protected veteran status or on the basis of disability, and Docebo takes affirmative action to employ and advance in employment qualified protected veterans and individuals with disabilities. Any individuals requiring a reasonable accommodation or would like to voluntarily disclose a disability or protected veteran status to assist with their employment application should send an e-mail to their recruiter directly.

Location: 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 GitLab’s Enablement & AI organization helps revenue teams build the knowledge, skills, tools, and confidence they need to sell GitLab effectively and deliver better customer outcomes. The team partners across Sales, Customer Success, Solutions Architecture, Partnerships, Product, Marketing, and Operations to turn business priorities—including product launches, new GTM motions, and AI adoption—into scalable programs, practical content, training, onboarding, and accreditations. It’s a high-impact, cross-functional team focused on improving field productivity, strengthening customer-facing capabilities, and measuring enablement’s contribution to business growth. This role supports GitLabs Customer Experience team and reports to the Vice President, Enablement & AI. What You'll Do Program manage and lead the build and execution of enablement programs to ensure internal customer success & professional services teams are equipped with content, resources, tools and training to effectively differentiate and sell the GitLab solution. Partner with field leadership and leverage CX resources across the globe to identify needs, collaborate on plans, and tailor/deliver content, customized to the nuances of the specific teams/markets. Scope and build new enablement content, including programs focused on product knowledge, skill development, onboarding, leadership development, and many other areas, specifically for the CX organization. Collaborate with the enablement content and enablement office, along with other SMEs to identify and develop core sales training and enablement curriculum, customized for CX, for various internal teams. Ensure alignment of enablement activities with key internal and external events, such as new product releases, campaigns, and essential industry trade shows. Leverage Salesforce, Cornerstone, Gong, and other tools to deliver training and educate the field on how to use specific tools in the region. Develop CX training job aids, supporting materials, and assessments to enhance field effectiveness across the CX organization. Measure and report on the effectiveness of enablement investments and the programs conducted. Determine opportunities for improving the learning experience and identify innovative techniques for delivery. Demonstrated progressive experience in a SaaS or software sales enablement role, preferably with expertise in DevOps and/or Open Source, with required experience supporting Public Sector, Federal, or SLED go-to-market teams in a government or regulated industry context. What You'll Bring Demonstrated progressive experience in a software sales, customer success, or enablement role. Ability to continuously meet due dates and execute on projects with positive impact from stakeholders. Experience building relationships with field leaders and their teams. Software sales or sales enablement experience, preferably with expertise in DevOps and/or Open Source. Working knowledge of sales training technology and methodologies; demonstrable experience with enablement concepts, practices, and procedures. Actively incorporates AI tools into daily practices to accelerate content development, program design, and ideation - and can model this behavior for the teams they support. Relevant experience preparing, developing, and executing sales effectiveness strategies, tactics and action plans. Ability to quickly understand technical concepts and explain them to audiences of varying technical expertise (sales team, customers, channel partners, and internal support partners). Strong ability to interact and influence effectively with field professionals and management. Exceptional written/verbal communication and presentation skills. Team player with strong interpersonal skills, skilled at project and change management and cross-functional collaboration. Ability to thrive in a fast-paced, unpredictable environment. Ability to use GitLab Ability to travel if needed for events such as team offsites or training. How GitLab will support you 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 Home office support 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. 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 $168,000 — $285,600 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, 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 Data Scientist at GitLab on the Enterprise Analytics team,  you’ll be a trusted analytical partner to Sales, Revenue Operations, and Finance, helping define how we measure go-to-market performance and where we invest to grow. This is a strategic and hands-on role. You’ll apply statistical, experimentation, and machine learning methods to forecast outcomes, explain what drives activation, conversion, expansion, and retention, and size opportunities. You’ll also support the company-level reporting and GTM performance views that executives use to run the business, covering consumption, ARR, and first orders. What you’ll do Embed yourself with business teams to become a trusted partner supporting insight generation and strategic decision making across GTM. Perform exploratory data analysis to uncover behavioral trends, long-term patterns, and the key drivers and levers behind business performance, and communicate their impact clearly to non-technical audiences. Build and productionize machine learning models - such as propensity, product-qualified lead (PQL) scoring, churn, and expansion models - including training, validation, testing, and feature engineering, using MLOps practices and tooling (CI/CD for ML pipelines, model registries, automated retraining, and monitoring) to move work reliably from notebook to production Design, run, and evaluate growth experiments (A/B tests and quasi-experiments) on onboarding, pricing and packaging, and upgrade flows, and measure their impact on activation, conversion, and retention Build and operationalize agentic workflows for analysis, modeling, and pipeline automation, with evaluation and monitoring that keep agent-generated insights accurate, traceable, and trustworthy. Contribute to GitLab’s Semantic Layer enabling stakeholders and agents to self-serve metrics using trusts and tested sources. Write production-grade Python and SQL that meets internal standards for style, maintainability, and performance in a high-scale database environment; maintain and advocate for these standards through code review What you’ll bring 3-5 years of professional experience in GTM analytics, data science, or a similar technical role Demonstrated ability to translate ambiguous business problems into clear, measurable questions and communicate technical concepts effectively to non-technical stakeholders. Experience with experimentation and causal inference (A/B testing, power analysis, quasi-experimental methods) and with statistical and machine learning methods such as regression, classification, clustering, and survival analysis Deep, hands-on understanding of SQL in cloud data warehouses (like Snowflake SQL), including working with product usage and event data, and in business intelligence tools (Looker, Tableau, Hex, or similar) Experience using Python for statistical modeling, machine learning, and production data science. With hands-on experience in pandas, NumPy, scikit-learn, Jupyter, and related libraries such as LightGBM and XGBoost Hands-on experience building agentic workflows with AI coding agents (e.g., Claude Code, OpenCode, or similar), including connecting agents to the right context, tools, and platforms such as MLflow, and evaluating their output for accuracy and reliability. Experience working in a B2C company working with motions and metrics, including Consumption, CRR, ARR, and Churn & Contraction Self-motivated and self-managing, with strong organizational skills Ability to use GitLab and to thrive in a fully remote organization About the Team The Enterprise Analytics team builds the trusted data products and insights behind GitLab’s Company wide sales, revenue, and finance reporting. We work across the business on metrics including First Orders, pipeline, CRR, ARR, and other key indicators, helping leaders make informed decisions and teams understand how their work contributes to GitLab’s growth. 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 $86,400 — $176,400 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, 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 Senior Manager, Data Science, you'll lead Product Data Science: a team of 6 Data Scientists within GitLab's data organization, reporting to the Director of Data Science. You have two mandates: Drive product impact now. Set the analytical agenda for your product areas and make sure the team's work changes decisions. Build the merged Data Science function. Define excellence for a Data Scientist who blends analytics and data science, and grow the team to that bar. You lead mainly through others, and step in hands-on when it matters: reviewing a model, pressure-testing an analysis, or writing the query yourself. What you’ll do Set a long-range vision and roadmap for Product Data Science, and show the team how its goals connect to company strategy Own prioritization and trade-offs across product areas, and adapt the team as priorities shift Be the go-to partner for Product and Engineering leaders on complex and urgent questions, choosing the right approach: a deep dive, an experiment, or a production model Raise risks and resource gaps early, and bring senior leaders clear options to drive timely decisions Hire, coach, and retain a high-performing team: build career paths, act on team feedback, and make tough talent decisions when needed Build a high-trust culture of urgency and accountability, where the team communicates openly, shares progress on a predictable cadence, and delivers quality results on time Set standards for experimentation, causal inference, metric definition, and production modeling What you’ll bring 10+ years in data science, product analytics, or a related field, including 3+ years managing data science or analytics teams in B2B SaaS or tech Strong product sense and a track record as a trusted partner to Product and Engineering leaders Exceptional communicator who makes complex problems and findings clear to any audience, from Product leaders to executives, and coaches others to do the same Thrives in ambiguity: structures undefined problems, gathers the right information, and makes sound decisions on high-risk, cross-team issues Courage to challenge: offers dissenting views, asks tough questions, and fosters inclusive debate Deep expertise in statistics and experimentation, including hands-on use of quasi-experimental methods (difference-in-differences, synthetic control, propensity score matching) Expert SQL (Snowflake preferred) and strong Python, with experience taking ML models to production Fluent with AI tools, with sound judgment on when AI output can be trusted Able to use GitLab, thrive in an all-remote, asynchronous company, model GitLab's remote working competencies, and work in line with GitLab's values Nice to Have Experience with developer tools, DevSecOps, or product-led growth products Experience measuring adoption and quality of AI-powered product features Thought leadership in data science or analytics, internally and externally Advanced degree in a quantitative field About the Team Product Data Science brings Data Science and Analytics together into one function. Our Data Scientists are business partners first, pairing strong product judgment with deep skill in SQL, Python, statistics, and machine learning. We help Product and Engineering decide what to build, measure what worked, and understand how customers get value from GitLab. The opportunity is growing fast. AI is driving growth in GitLab's consumption business, creating new ways for data to drive growth. As AI takes over routine reporting, the team focuses on the hard problems: experimentation, causal inference, production models, and recommendations leaders act on. 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 .

Location: Remote, Canada 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. As a Commercial Account Executive, Mid-Market, you’ll be the primary point of contact for prospective and existing customers in our mid-market segment, helping organizations modernize how they plan, build, secure, and ship software with GitLab’s AI-powered DevSecOps platform. You’ll own a broad book of business in your territory and serve as a strategic, trusted advisor to your accounts as you prospect, run complex sales cycles, and guide customers on their journey with GitLab to achieve clear business outcomes while supporting adoption and reducing churn. You’ll collaborate closely with Sales Development, Solutions Consultant, Renewals, Partners, and Sales leadership, using value-based selling and structured sales methodologies (such as MEDDPICC) to build a healthy pipeline, run accurate forecasts, and support revenue goals across a wide range of deal sizes. Must be located in Canada. What you’ll do Own and manage a broad Commercial book of business as the primary point of contact in your territory, focusing only on expansion opportunities. Focus on customer accounts with with low to modest current investments in Gitlab in an effort to grow and expand our partnership Articulate the value of GitLab’s AI-powered DevSecOps platform to Commercial prospects and customers, tailoring messaging to their business and technical needs. Build and maintain a healthy pipeline through consistent prospecting, qualification, and advancement of opportunities, using structured methodologies (such as MEDDPICC and Command of the Message) to support your pipeline and revenue goals. Document buying criteria, decision processes, next steps, and key stakeholders to run disciplined, well-orchestrated sales cycles. Collaborate with sales development, customer success, renewals, marketing, technical teams, and partners to deliver a cohesive pre- and post-sales experience, co-sell and close opportunities, and expand GitLab’s footprint while delivering added value for customers. Support customer adoption of GitLab solutions, proactively work to reduce churn and contraction, and participate in quarterly forecasting and territory planning. Contribute to continuous improvement by sharing win/loss insights, updating the sales handbook, and being a clear voice of the customer into the product via our public issue tracker. What you’ll bring Experience selling SaaS solutions by leading value-based conversations with technical and business stakeholders, ideally including development or DevSecOps teams. Ability to manage a broad mid-market territory as the primary point of contact, owning a book of business from prospecting through close, adoption, and expansion. Skill in building and maintaining strong customer relationships, including effective discovery, negotiation, and closing to support long-term customer outcomes. Comfortable driving consistent outbound prospecting activity, creating and maintaining a healthy pipeline, and maintaining accurate territory and forecast documentation. Ability to collaborate closely with cross-functional partners (sales development, customer success, renewals, marketing, partners, and technical teams) to coordinate account strategies. Clear and structured communication skills, including presenting the GitLab value proposition to different audience levels and documenting customer insights and lessons learned. Interest in GitLab, open source, and tools that support software development, with the ability to connect customer business challenges to GitLab’s DevSecOps platform. The ability to travel for events such as trainings, team off sites, customer meetings, etc. About the team The Commercial Account Executive - Mid-Market role focuses on helping mid-market customers adopt and expand their use of our AI powered DevSecOps platform. You’ll be part of a dedicated Canadian team of Account Executives, Sales Development, Solution Consultants, Renewals, and Partners to manage a broad book of business and a wide range of opportunity sizes. Our mission is to guide customers through their journey with GitLab, from first evaluation to long term value realization, by developing new business, strengthening customer relationships, and supporting healthy product adoption. We collaborate closely through shared playbooks, our sales handbook, and GitLab itself to stay aligned on territory plans, pipeline health, and best practices. For more on how we work, see the Commercial Account Executive Handbook . Remote-Global 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: San Francisco, CA; Bellevue, Wa Workplace: Hybrid About Niantic Spatial We are building for the >80% of economic activity that happens beyond the reach of screens. AI has learned from the text, images and video online, but it still lacks an accurate understanding of physical space. That’s one of the biggest unsolved problems in AI, and it’s the one we’re solving at Niantic Spatial. We build spatial AI models and services so people and machines can reason, learn and act safely in the physical world. We turn camera imagery, video, sensor data and archives into accurate, AI-readable representations of real places that robots can train in and machines can use to know exactly where they are. In physical AI, mistakes have real consequences. That’s why we build AI grounded in measured reality, not guesswork, so the people and machines relying on it can trust it to get things right. Our team built some of the world’s most widely used maps. Now we’re building something bigger: a living, measured record of the real world that machines can query, learn from and use to understand how places change over time. If you want to help AI understand the world we actually live in, come build with us. About the Role You’ll join a small infrastructure team with broad, shared ownership — the engineers who keep Niantic Spatial running. The team covers the cloud platform, the developer tooling every engineer depends on, and the edge services our customers’ requests pass through. You’ll work across SRE, infrastructure, and developer platform alongside teammates who know the stack well, and you’ll grow into owning parts of it yourself. Because every engineer here builds on what this team provides, your work will also shape how the whole engineering org builds, ships, and operates. What You'll Do - Cloud and SRE: Build and maintain cloud infrastructure as code, and help improve reliability through monitoring, alerting, and service-level objectives. - Developer Platform: Help run our source control, CI/CD pipelines, and build infrastructure so engineers can ship quickly and safely. - Production Operations: Share on-call, take part in incident response and follow-up, and automate away repetitive operational work. - Edge and Delivery: Help run the edge API gateway, CDN, and authentication and authorization systems with the rest of the team. - Compute and GPU Management: Help provision and monitor compute and GPU capacity across teams. - AI-Assisted Operations: Use AI tools to help build, automate, and maintain our infrastructure, and help shape how the team uses them. What You'll Bring - Years of Experience: 3+ years in infrastructure, SRE, DevOps, or platform engineering. - Education: Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. - Infrastructure as Code: Experience managing infrastructure as code with tools such as Terraform, Pulumi, or similar. - Cloud: Hands-on experience with GCP, AWS, or another major cloud provider in production. - CI/CD: Experience building and maintaining CI/CD pipelines in GitLab, GitHub Actions, or similar. - Containers: Production experience with containers and container orchestration, such as Kubernetes. - Core Technical Skills: Proficiency in at least one programming language such as Python, Go, TypeScript, or C++, plus shell scripting and Linux systems. - AI in Your Workflow: Comfort using AI-assisted tools in your engineering work, or a strong interest in building that habit. We’ll help you ramp up on how we use AI here. Nice to Have - Familiarity with API gateways, load balancers, or CDNs. - Familiarity with modern authentication and authorization, such as OAuth 2.0, OIDC, or cloud IAM. - Experience with GPU workloads or ML infrastructure. - Experience with message queuing systems. Location & Work Model This role is based in our San Francisco or Sunnyvale, CA office, or in Bellevue, WA. We work in a high-collaboration environment and ask team members to be on-site a minimum of 3 days per week. Compensation & Benefits The base salary range for this position is $171,000 - $230,000 for Bay Area candidates and $162,500 - $218,500 for Seattle/Bellevue candidates. Actual salary is based on assessed skills, experience, and location. This role is also eligible for equity, bonus, and benefits. Your recruiter can answer questions about total compensation during the hiring process. Inclusive Application We know the strongest candidates don't always tick every box. If you're excited about this role and believe you could do it well, we encourage you to apply even if your experience doesn't match every qualification listed — you may be exactly who we're looking for. Equal Opportunity Niantic Spatial is an equal opportunity employer. Individuals seeking employment at Niantic Spatial are considered without regard to race, color, ancestry, national origin, religion, creed, age, gender (including pregnancy, childbirth, breastfeeding or related medical conditions), marital status, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, sexual orientation, or any other protected category under applicable laws. Niantic Spatial will also consider qualified applicants with criminal histories in accordance with applicable laws. Please contact your recruiter if you want to request an accommodation for the job application or interview process. Candidate Privacy I understand that by submitting my job application, the information I provide as part of that application will be used in accordance with Niantic Spatial's Privacy Notice for Job Applicants and Candidates https://www.nianticspatial.com/applicant-privacy-notice.

Location: Ukraine; Spain; Slovakia; Serbia; Yerevan; Slovenia; Poland Workplace: remote Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide. Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits You will work in a small, senior pod alongside an FDE and an FDX,  Forward Deployed Executives (FDX) own the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs. Forward Deployed Engineers (FDE) embed with a client, map the client workflow, identify the business problem underneath it, design and build a working AI solution, present to the client, and transfer the knowledge to the client's team. Owns technical direction of the whole solution. Senior AI Engineer. When an FDE comes back from the client with the business problem, you will help turn that into an agentic system that runs in production and will be responsible for evaluation, observability, and guardrails.  You'll have real ownership of components and of the technical decisions inside them. Requirements: Mindset Proactive and self-directed; you push for clarity rather than waiting for a ticket Excellent communication and problem-solving skills Comfort with ambiguity and ownership. B2+ English, comfortable collaborating across distributed, multicultural teams. Technical depth 5+ years in software or ML engineering, with production systems you were accountable for. Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes. Shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks. Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks. Experience building and optimizing RAG systems in production. Strong engineering fundamentals. Full-stack mindset, comfortable across AI, backend development, and cloud infrastructure. Python and/or TypeScript proficiency; depth matters more than stack. Dropped into an unfamiliar codebase, you're productive. Hands-on AWS in production: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus. Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines. You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release. Model and agent monitoring, drift detection. Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs. Hands-on production experience with the Claude ecosystem —  Claude Code, CLAUDE.md, hooks, skills files.  Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus. MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus. Nice to Have: Experience in one of the industries: financial services, insurance, healthcare. Consulting, professional services, or other embedded customer-facing delivery. AWS and Claude Code Certifications A2A: you can explain agent-to-agent interoperability CI/CD pipeline experience (GitHub Actions, GitLab CI) Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines. Experience in an additional language (Go, TypeScript, or Rust). Experience with Apache Spark, Apache Airflow, Kafkа Responsibilities: Work in a pair with an FDE and an FDX. Build and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Build and optimize RAG systems for production use cases Build the evaluation harness before you build the feature. Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer. Integrate AI components into backend services and RESTful APIs Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD. Implement LLMOps and AgentOps practices: agent tracing, prompt and version management, cost and latency monitoring, regression testing, drift detection Start from the blueprint, contribute to enablement and handover: clear documentation, runbooks, and pairing with the client engineers who will inherit the system. Feed reusable components and lessons back into the Provectus Blueprints Participate in technical discussions and architectural decisions Conduct model evaluation, improve failure modes you find, optimize model performance, efficiency, and reliability Mentor junior and mid-level AI engineers, conduct code reviews and share knowledge across the team through documentation, presentations, and workshops. What We Offer: The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside FDE and FDX A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work How we hire: Intro conversation. The role, your background and aspirations, tech questions. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant HR Interview. Soft skills and expectations HM interview. Tech questions; a live engineering session is also possible

Location: North Macedonia; Bosnia and Herzegovina; Czechia; Croatia; Moldova; Bulgaria; Montenegro Workplace: remote Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide. Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits You will work in a small, senior pod alongside an FDE and an FDX,  Forward Deployed Executives (FDX) own the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs. Forward Deployed Engineers (FDE) embed with a client, map the client workflow, identify the business problem underneath it, design and build a working AI solution, present to the client, and transfer the knowledge to the client's team. Owns technical direction of the whole solution. Senior AI Engineer. When an FDE comes back from the client with the business problem, you will help turn that into an agentic system that runs in production and will be responsible for evaluation, observability, and guardrails.  You'll have real ownership of components and of the technical decisions inside them. Requirements: Mindset Proactive and self-directed; you push for clarity rather than waiting for a ticket Excellent communication and problem-solving skills Comfort with ambiguity and ownership. B2+ English, comfortable collaborating across distributed, multicultural teams. Technical depth 5+ years in software or ML engineering, with production systems you were accountable for. Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes. Shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks. Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks. Experience building and optimizing RAG systems in production. Strong engineering fundamentals. Full-stack mindset, comfortable across AI, backend development, and cloud infrastructure. Python and/or TypeScript proficiency; depth matters more than stack. Dropped into an unfamiliar codebase, you're productive. Hands-on AWS in production: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus. Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines. You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release. Model and agent monitoring, drift detection. Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs. Hands-on production experience with the Claude ecosystem —  Claude Code, CLAUDE.md, hooks, skills files.  Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus. MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus. Nice to Have: Experience in one of the industries: financial services, insurance, healthcare. Consulting, professional services, or other embedded customer-facing delivery. AWS and Claude Code Certifications A2A: you can explain agent-to-agent interoperability CI/CD pipeline experience (GitHub Actions, GitLab CI) Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines. Experience in an additional language (Go, TypeScript, or Rust). Experience with Apache Spark, Apache Airflow, Kafkа Responsibilities: Work in a pair with an FDE and an FDX. Build and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Build and optimize RAG systems for production use cases Build the evaluation harness before you build the feature. Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer. Integrate AI components into backend services and RESTful APIs Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD. Implement LLMOps and AgentOps practices: agent tracing, prompt and version management, cost and latency monitoring, regression testing, drift detection Start from the blueprint, contribute to enablement and handover: clear documentation, runbooks, and pairing with the client engineers who will inherit the system. Feed reusable components and lessons back into the Provectus Blueprints Participate in technical discussions and architectural decisions Conduct model evaluation, improve failure modes you find, optimize model performance, efficiency, and reliability Mentor junior and mid-level AI engineers, conduct code reviews and share knowledge across the team through documentation, presentations, and workshops. What We Offer: The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside FDE and FDX A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work How we hire: Intro conversation. The role, your background and aspirations, tech questions. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant HR Interview. Soft skills and expectations HM interview. Tech questions; a live engineering session is also possible

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 Compensation Manager at GitLab, you'll lead the design, planning, and execution of compensation programs that help us attract, retain, and reward team members. You'll own recurring programs, including the annual focal merit cycle, and provide guidance and oversight for promotion cycles, quarterly equity grant cycles, and semi-annual bonus programs. Working closely with Total Rewards leadership and partners across People, Finance, and Legal, you'll turn program objectives into clear deliverables, establish processes and controls, and see complex cycles through from planning to closeout. Your work will help ensure accurate, timely delivery and a clear experience for leaders, People teams, and team members. You'll be based in the United States. We prefer a West Coast location to support collaboration with stakeholders across time zones. What you’ll do Lead compensation programs from design and readiness through approvals, processing, communication, and post-cycle review, including ownership of the annual focal merit cycle and oversight of promotion, quarterly equity, and semi-annual bonus cycles. Define program calendars, decision points, responsibilities, controls, and success measures. Coordinate dependencies and keep stakeholders informed of progress, risks, and decisions. Ensure compliance with eligibility rules and develop process documentation, manager resources, and communications. Advise People Business Partners, Talent Acquisition, and leaders on program application and exceptions, escalating policy and governance decisions when needed. Analyze compensation data and program outcomes, develop recommendations for Total Rewards leadership, and partner with Finance on budgeting, cost modeling, and reconciliation. Partner with People Technology and IT systems stakeholders to improve workflows, reporting, and usability. Validate inputs and outputs, ensure timely processing, maintain audit and control documentation, and protect confidential compensation information. Oversee the annual refresh of global compensation and equity ranges to ensure accuracy, and support compensation partners with program delivery and analysis. Lead improvements that reduce program risks and friction, strengthen consistency and transparency, and improve the team member experience. Use clear documentation and asynchronous communication to coordinate work across time zones. What you’ll bring Experience designing and operating compensation programs, with expertise in corporate compensation and public company equity and a record of delivering complex merit, equity, bonus, or promotion cycles accurately from planning through closeout. Strong analytical and spreadsheet skills, including interpreting compensation data, building scenarios, checking assumptions, and explaining findings to decision-makers. An understanding of compensation governance, data integrity, and controls, with discretion and sound judgment when handling confidential information and sensitive decisions. The ability to translate policy and strategy into operating procedures, system requirements, and stakeholder guidance, plus experience with human resources information systems and compensation planning tools such as Pave and Workday, and comfort working on a Mac. Attention to detail, practical problem-solving skills, and the persistence to work through complex issues and deliver accurate outcomes. You can learn unfamiliar programs, systems, and business contexts quickly. The ability to build trusted partnerships, advise leaders and People teams, resolve ambiguity, and move decisions forward without relying on formal authority. Strong written and verbal communication skills and the ability to coordinate with global partners across time zones using asynchronous practices. Helpful, but not required: experience supporting a global, distributed workforce, including partners in India or other locations outside the United States; compensation-cycle communications; and experience in a software or technology company. About the team The current Compensation team consists of 2 Global Compensation Partners and a Lead Total Rewards Program Manager that collaborates with the Compensation and Benefits teams. We provide compensation programs for 40+ countries globally. Our compensation work brings together People Business Partners, Talent Acquisition, People Operations, and People Technology. We use clear written communication and collaboration to coordinate across a distributed workforce and time zones. 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 .

🧩 Требования: уверенное знание C# и .NET, коммерческий опыт от 3 лет, опыт разработки backend‑сервисов на Core, владение REST API и gRPC, понимание принципов проектирования ПО и написания тестируемого кода; опыт работы с PostgreSQL, MongoDB, Redis/KeyDB, брокерами сообщений (Kafka или RabbitMQ), Docker и Kubernetes;

Задачи: — Развёртывать и сопровождать приложения совместно с командами разработки. — Поддерживать CI/CD‑процессы с использованием GitLab, Jenkins, Ansible, Docker Swarm, Kubernetes, Helm, Terraform, Yandex Cloud. — Управлять секретами и доступом через HashiCorp Vault, RBAC в Kubernetes и GitLab. — Настраивать политики безопасности в Kubernetes (PodSecurity, Network Policies, OPA/Gatekeeper). — Развивать инструменты контроля безопасности цепочки поставок ПО. — Участвовать в реагировании на инциденты информационной безопасности и R&D‑задачах. — Диагностировать проблемы, работать с системами мониторинга и диагностики (Zabbix, ELK, Mimir, Grafana, Loki). — Автоматизировать процессы сопровождения и поддерживать документацию. Требования: — Уверенные знания Linux, включая Astra Linux, в области администрирования и безопасности. — Высокий уровень владения Bash. — Понимание принципов авторизации и аутентификации. — Опыт работы с реляционными и нереляционными базами данных. — Опыт работы с GitLab CI. — Знание сетевых технологий (TCP/IP, модель OSI), принципов безопасности сетей, виртуализации и контейнеризации. — Понимание современных угроз информационной безопасности, методов и средств защиты информации. — Знание методологии оценки уязвимостей (CVSS, EPSS) и их классификации (CWE). — Опыт организации процессов разработки ПО (git, ветвление кода, CI/CD). — Опыт работы с Kafka и RabbitMQ. — Опыт работы с системами сбора логов (EFK/ELK, Grafana Loki) и мониторинга (Prometheus, Grafana). Плюсом: — Знание Golang или Python для автоматизации. — Опыт работы с Openstack. — Опыт работы в условиях импортозамещения.

Location: Ukraine; Serbia; Yerevan; Spain; Slovakia; Slovenia; Poland Workplace: remote Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide. Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits You will work in a small, senior pod alongside an FDX; our delivery arc is Sprint → Enable → Realize: Forward Deployed Executive (FDX) owns the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs — revenue growth, cost reduction, risk reduction. Forward Deployed Engineer (FDE) embeds with a client to change how that client operates. You own the method; nobody hands you a ticket. You map the client workflow as it actually happens, identify the business problem underneath it, build a working AI solution, present to the client in the language of outcomes, and transfer it. Provectus maintains industry Blueprints — working systems that have already shipped for a client in the same industry — so you begin from running code and tuning it to this client's specific book, regulators, and operating posture. You will be measured on whether the Business Unit's number moved, not on hours or scope delivered. What You’ll Do: Take the seat Sit with the client and the Forward Deployed Executive at the start of an engagement. Learn the function from inside, not from a requirements doc, and redesign the function from first principles. Reach working fluency in a new domain — insurance underwriting, healthcare revenue cycle, asset flow. Build Design and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Implement and optimize RAG systems for production use cases Build the evaluation harness before you build the feature. Define what working means, instrument it, and let the evals drive the design. Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer. Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD, automated testing, monitoring, and maintainable after we leave. Hand the system over to the client. Start from the blueprint, and feed the blueprint. What you learn in the field becomes the baseline the next engagement starts from. Lead architecture reviews, produce technical design documents, and contribute to standards. Mentor engineers and share knowledge across the team. Own the outcome. Work in a pair with a FDX who carries the Business Unit’s KPIs. Your work is measured against the same number. Own the technical direction of technical proposals and scoping. Drive adoption. Change management is part of the engineering job here. Be credible with the customer’s engineers and their executives. Shape what we commit to before we commit to it. What You’ll Bring: Mindset Proactive and self-directed; identify problems before they're handed to you Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job B2+ English, comfortable collaborating across distributed, multicultural teams Client Engagement You are willing to spend time understanding and doing someone else’s job on the client's side before you write a line of code Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO, presenting outcomes to them You can produce a scoped, phased delivery plan with clear deliverables, dependencies, and risks — and estimate what it will cost to build and to run Technical depth 7+ years building and running production systems. Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes Designed and shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks. Experience building and optimizing RAG systems in production Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack. Experience in making and defending architectural trade-off decisions Hands-on AWS production depth: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release Model and agent monitoring, drift detection Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs Hands-on production experience with the Claude ecosystem —  Claude Code, CLAUDE.md, hooks, skills files.  Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus Nice to have: Prior experience as a founder, CTO, or engineering leader who has chosen to return to individual contribution Experience in one of the industries: financial services, insurance, healthcare Consulting, professional services, or other embedded customer-facing delivery A2A: you can explain agent-to-agent interoperability AWS and Claude Code Certifications CI/CD pipeline experience (GitHub Actions, GitLab CI) Experience in an additional language (Go, TypeScript, or Rust) Experience with Apache Spark, Apache Airflow, Kafkа What We Offer: The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside Principal Architects and Forward Deployed Engineers A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work How we hire: Intro conversation. The role, your background and aspirations, tech questions. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant HR Interview. Soft skills and expectations HM interview. Tech questions; a live engineering session is also possible

Location: North Macedonia; Montenegro; Moldova; Bulgaria; Czechia; Bosnia and Herzegovina; Croatia Workplace: remote Provectus is an AWS Premier Partner and an Anthropic Strategic Partner , working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide. Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits You will work in a small, senior pod alongside an FDX; our delivery arc is Sprint → Enable → Realize: Forward Deployed Executive (FDX) owns the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs — revenue growth, cost reduction, risk reduction. Forward Deployed Engineer (FDE) embeds with a client to change how that client operates. You own the method; nobody hands you a ticket. You map the client workflow as it actually happens, identify the business problem underneath it, build a working AI solution, present to the client in the language of outcomes, and transfer it. Provectus maintains industry Blueprints — working systems that have already shipped for a client in the same industry — so you begin from running code and tuning it to this client's specific book, regulators, and operating posture. You will be measured on whether the Business Unit's number moved, not on hours or scope delivered. What You’ll Do: Take the seat Sit with the client and the Forward Deployed Executive at the start of an engagement. Learn the function from inside, not from a requirements doc, and redesign the function from first principles. Reach working fluency in a new domain — insurance underwriting, healthcare revenue cycle, asset flow. Build Design and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Implement and optimize RAG systems for production use cases Build the evaluation harness before you build the feature. Define what working means, instrument it, and let the evals drive the design. Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer. Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD, automated testing, monitoring, and maintainable after we leave. Hand the system over to the client. Start from the blueprint, and feed the blueprint. What you learn in the field becomes the baseline the next engagement starts from. Lead architecture reviews, produce technical design documents, and contribute to standards. Mentor engineers and share knowledge across the team. Own the outcome. Work in a pair with a FDX who carries the Business Unit’s KPIs. Your work is measured against the same number. Own the technical direction of technical proposals and scoping. Drive adoption. Change management is part of the engineering job here. Be credible with the customer’s engineers and their executives. Shape what we commit to before we commit to it. What You’ll Bring: Mindset Proactive and self-directed; identify problems before they're handed to you Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job B2+ English, comfortable collaborating across distributed, multicultural teams Client Engagement You are willing to spend time understanding and doing someone else’s job on the client's side before you write a line of code Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO, presenting outcomes to them You can produce a scoped, phased delivery plan with clear deliverables, dependencies, and risks — and estimate what it will cost to build and to run Technical depth 7+ years building and running production systems. Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes Designed and shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks. Experience building and optimizing RAG systems in production Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack. Experience in making and defending architectural trade-off decisions Hands-on AWS production depth: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release Model and agent monitoring, drift detection Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs Hands-on production experience with the Claude ecosystem —  Claude Code, CLAUDE.md, hooks, skills files.  Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus Nice to have: Prior experience as a founder, CTO, or engineering leader who has chosen to return to individual contribution Experience in one of the industries: financial services, insurance, healthcare Consulting, professional services, or other embedded customer-facing delivery A2A: you can explain agent-to-agent interoperability AWS and Claude Code Certifications CI/CD pipeline experience (GitHub Actions, GitLab CI) Experience in an additional language (Go, TypeScript, or Rust) Experience with Apache Spark, Apache Airflow, Kafkа What We Offer: The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside Principal Architects and Forward Deployed Engineers A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work How we hire: Intro conversation. The role, your background and aspirations, tech questions. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant HR Interview. Soft skills and expectations HM interview. Tech questions; a live engineering session is also possible

🕹 Список обязанностей: Развёртывание и администрирование Kubernetes-кластеров на bare metal. Настройка и оптимизация Docker-контейнеризации.

– Опыт разработки на Java 17+; – Опыт применения Spring Boot (Spring Data, Spring Kafka);

Location: Remote Workplace: Remote More than 30,000 subscription apps run on Adapty: $5B in revenue tracked, 4B users served, 80B API calls a month. That's one of the richest datasets in the app economy. Our mission is simple: make apps rich. We are a team of 210+ passionate, product-driven people who love solving big challenges. Backed by top investors like 500 Startups and Surface Ventures, we are building one of mobile's fastest-growing SaaS companies and aiming for number one worldwide. Why this role matters Adapty runs on infrastructure we own and operate ourselves: a Proxmox and Ceph platform across OVH, Hetzner and bare metal, with parts of the stack in AWS and GCP. That platform processes billions of dollars of subscription volume a year, and today too much of it depends on a single engineer. You are joining to take that platform over: fully owned, fully described in code, and cheap to run at scale. In your first months you will own Proxmox and Ceph end to end, drive resource rightsizing, and lead the split of our development workloads into a separate cluster. What you'll do - Own our Proxmox and Ceph platform end to end — capacity, upgrades, performance and incident response - Run infrastructure across OVH, Hetzner and bare metal, alongside workloads in AWS and GCP - Drive resource rightsizing: find where we overpay, size it correctly, and prove the saving in the bills - Lead the separation of development workloads into a dedicated cluster, without downtime for production - Keep everything as code — Terraform, Ansible, ArgoCD and GitLab CI, with no manual changes in production - Own reliability: on-call, incident response, root cause analysis and the runbooks that follow - Support the data layer our product runs on — PostgreSQL, ClickHouse, Aerospike About you - 10+ years working with infrastructure and physical hardware, not only managed cloud - 5+ years running Kubernetes and cloud platforms in production - Hands-on with bare metal and providers like OVH and Hetzner, plus AWS and/or GCP - Strong with Terraform, Ansible, ArgoCD and GitLab CI — you describe infrastructure in code by default - Real FinOps experience: you can name what infrastructure cost before and after you touched it - You take problems all the way to the root cause and to the fix, including outside your formal scope - You say things directly — risks and bad news arrive early, not after the incident Nice to have - Production experience with Proxmox and Ceph specifically - PostgreSQL, ClickHouse or Aerospike at scale - Experience splitting shared environments into isolated clusters - Building observability and on-call practice from scratch - High-load B2B SaaS background WHAT'S IN IT FOR YOU - Strong product with industry-best metrics. Adapty is among the top 5% fastest-growing SaaS companies. - Exceptional compensation directly tied to your results. - Direct communication and ownership. No bureaucracy, no politics, just impact. - Flexible remote work. Join us from anywhere or work onsite in our Belgrade or London offices. - Professional support. Language learning, sports, health insurance, laptop coverage, and more.

Ищем Senior/Middle+ Golang Developer.

Задачи: — Качественная разработка на языке PHP 8.4+ на базе модифицированного фреймворка Yii 1.1 с использованием Vue.js 3+ (full-stack) — Проектирование реляционных структур хранения данных на PostgreSQL, оптимизация запросов, создание индексов — Программирование сложных математических алгоритмов, включая расчет тарифов и агрегирование данных для графиков — Написание оптимального кода Требования: — Опыт работы от 5 лет в роли разработчика — Уверенное владение PHP 8+ — Знание ООП и паттернов проектирования — Глубокий опыт работы с реляционными базами данных PostgreSQL — Владение Yii 1.1 и Vue.js 3+ — Опыт работы с Kafka — Навыки работы с Git и Gitlab — Опыт использования Docker — Знания математики и логики — Наличие высшего образования в области математики или технической специальности