Senior AI Engineer | JobSetuu
GitLab
Posted 12 hours ago • Via jobicy.com
Description
Job Overview
- Source: Jobicy
Job Description
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 AI Engineer at GitLab, you'll help build the foundation for GitLab's transformation into an AI-first company. Reporting to the Director, Enterprise AI, you'll be a hands-on technical leader responsible for delivering internal AI-powered solutions that drive measurable business outcomes.
Building fast matters, but it's not enough on its own. This role starts with understanding the real problem: mapping how work moves across teams, tools, and handoffs, identifying the true constraint, and validating whether AI is the right solution before you begin development. From there, you'll take ownership from discovery through deployment, combining strong engineering skills with systems thinking and business understanding.
Your initial focus will span Sales, Marketing, and Customer Support, where you will embed AI solutions into key systems and workflows. This role offers the opportunity to shape how GitLab team members work, improve flow across the organization, and help advance our mission in a remote, asynchronous, and values-driven environment.
What you'll do
- Diagnose business problems before building solutions. Map workflows, identify constraints, and confirm whether AI is the right intervention. Be prepared to say "this doesn't need AI" when that's the honest answer.
- Own AI initiatives end-to-end, from stakeholder discovery and technical design through implementation, deployment, and iteration.
- Design, develop, and ship AI-powered solutions quickly, delivering working prototypes in days, not months, with a focus on practical outcomes and measurable business value.
- Improve organizational flow by building solutions that reduce bottlenecks, shorten lead times, and increase throughput. Measure success using flow metrics alongside adoption and ROI.
- Integrate AI capabilities into existing systems and workflows using APIs, orchestration tools, and modern AI platforms, including GitLab Duo Agent Platform, where appropriate. The right tool wins, whether that's custom code, a platform, or a well-crafted prompt.
- Be Customer Zero: leverage and showcase GitLab's AI offerings wherever possible, feeding real-world usage insights back to R&D.
- Partner closely with stakeholders across functions to understand the real constraints. Ask the right questions, bridge technical and non-technical perspectives, and align on outcomes before jumping to solutions.
- Define and track success through business metrics, flow metrics, and feedback loops that make performance visible and actionable.
- Contribute to technical direction by evaluating tools, documenting patterns, and creating reusable foundations that help the team scale its impact.
What you'll bring
- A Technologist at Heart - Genuinely invested in technology, the foundational and the cutting-edge in equal measure. You're as energised by a well-designed API integration as you are by the latest foundation model release. You reach for the simplest solution that solves the problem well, rather than forcing new technology when proven approaches would do. AI is a powerful part of your toolkit, but it sits on top of solid engineering fundamentals, not in place of them.
- Competent, Confident Coding Skills - You can build working solutions end-to-end, write clean and maintainable code, and debug effectively. Whether your skills were honed in a traditional engineering role, through building automations, or shipping side projects, what matters is that you can deliver production-quality work independently.
- AI & LLM Technical Depth - Strong proficiency in at least one modern scripting language (Python, JavaScript/TypeScript, or similar) and a solid understanding of REST APIs, GraphQL, and integration patterns. Deep, practical experience with modern AI technologies, specifically: Prompt engineering as a core discipline: designing effective system prompts, managing context windows, structuring multi-turn interactions, evaluating output quality, and iterating systematically on prompt design.
- Model selection and cost-performance trade-offs: understanding when a smaller fine-tuned model outperforms a general-purpose large one, when RAG is the right architecture versus expanding the context window, and how to make principled decisions about capability versus cost.
- Agentic architecture patterns: tool use, multi-agent orchestration, human-in-the-loop designs, guardrails, evaluation frameworks, and production-grade reliability patterns.Practical fluency across the LLM ecosystem: hands-on experience with models from Anthropic, OpenAI, open-source alternatives, and the judgment to know which to reach for and when.
- AI Safety & Risk Awareness - You think critically about how the solutions you build could be exploited, misused, or produce unintended consequences. You know how to design appropriate guardrails (input validation, output filtering, access controls, prompt injection defences, and data leakage prevention) and you treat these as first-class engineering concerns.
- Systems Thinking & Diagnostic Rigour - The ability to look at a complex process and see the constraint. Comfortable mapping how work flows end-to-end, identifying bottlenecks, and tracing problems to root causes before proposing solutions. You instinctively ask "what's actually blocking flow here?" before asking "what model should I use?"
- Business System Expertise - Familiarity with the landscape of enterprise business systems, CRM (Salesforce), marketing automation (Marketo), support platforms (Zendesk), integration and orchestration tools (Workato), AI platforms (Relevance AI), and enterprise search and knowledge tools (Glean). You don't need deep experience with all of these, but to understand what they do, how they fit together, and be willing to build with and across them. A strong understanding of enterprise data models and workflows is essential.
- Broad Functional Understanding - Ability to have meaningful conversations with stakeholders across diverse domains and quickly understand their unique needs.
- End-to-End Ownership - Track record of owning complex initiatives from discovery through delivery. Comfortable operating with ambiguity and driving to measurable outcomes independently.
- Product Mindset - Ability to scope MVPs, prioritise ruthlessly, and deliver iteratively. In addition, consider adoption, user experience, and business outcomes.
Preferred requirements
- Experience with GitLab platform and CI/CD workflows
- Background in consulting, solutions engineering, or customer-facing technical roles
- Familiarity with value stream mapping, flow metrics, or Theory of Constraints thinking
- Experience with low-code/no-code orchestration tools (n8n, Make, Workato) alongside custom development
- Previous startup or high-growth company experience
- Experience mentoring or leading technical projects with junior engineers
About the team
You will join the Enterprise Technology & AI team. We're the backbone of the organisation, driving transformation in how GitLab team members make decisions, operate at scale, and deliver results for our customers.
We believe the best AI solutions start with understanding the system, not the technology. We value people who think in constraints and flow, who build with conviction, and who never stop learning. We work in an all-remote, asynchronous setting, guided by GitLab's values of collaboration, results, efficiency, diversity, inclusion and belonging, iteration, and transparency.
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.
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.
Expert Career Tips for Senior AI Engineer Roles
To succeed in a competitive market as a Senior AI Engineer, you need more than just technical skills. Here are some expert strategies to elevate your profile:
- Build a Strong Portfolio: For technical roles, a clean GitHub or a personal project site is essential. For non-technical roles, a case study portfolio demonstrating problem-solving and impact is equally valuable. Show, don't just tell, what you have achieved in your previous positions.
- Master the Narrative: When interviewing, use the STAR method (Situation, Task, Action, Result) to structure your answers. Quantify your results wherever possible—mentioning "increased efficiency by 20%" is much more impactful than saying "improved efficiency."
- Continuous Learning: The industry moves fast. Whether it's staying updated with the latest AI tools or mastering a new management methodology, continuous professional development is key. Consider obtaining industry-recognized certifications that align with Senior AI Engineer requirements.
- Networking: Connect with other professionals in similar roles. Join online communities, attend webinars, and engage in meaningful discussions on professional social networks. Often, the best opportunities come through referrals and community engagement.
- Soft Skills Matter: Communication, empathy, and leadership are often the deciding factors between two equally qualified technical candidates. Cultivate these skills as they are universally valued across all industries and seniority levels.
Additionally, research the specific company's culture and values. Tailoring your application to show how you align with their mission can significantly increase your chances of moving forward in the process.
Salary & Compensation
Salary not disclosed; typically competitive for the role.
Work Arrangement
Type: On-Site
Standard business hours at the office.
Comprehensive Application Strategy & Hiring Process
Applying for a new role is a marathon, not a sprint. Follow this strategic approach to maximize your success rate:
1. Initial Research & Tailoring
Don't send the same resume to every employer. Spend at least 30 minutes researching the company. Look for recent news, their product roadmap, and their team structure. Modify your summary and core competencies to reflect the specific keywords found in the job description.
2. The Perfect Cover Letter
If the application allows for a cover letter, use it to tell a story that your resume cannot. Explain why you are passionate about this specific company and how your unique background makes you the perfect fit for the challenges they are currently facing.
3. Navigating the Multi-Stage Interview
Most modern hiring processes involve 3-5 stages. This typically includes a recruiter screen, a technical or skill-based assessment, a peer interview, and a final leadership round. Prepare for each stage differently: focus on enthusiasm and fit for the recruiter, technical depth for the assessment, and strategic vision for the leadership round.
4. Post-Interview Follow-Up
Always send a personalized thank-you note within 24 hours of each interview. Reference a specific topic discussed during the call to demonstrate your active listening and genuine interest in the role.
By following these steps, you demonstrate a high level of professionalism and attention to detail that sets you apart from the average applicant.
Typical Interview Process
- Resume screening
- HR call
- Skill interview
- Final manager interview
- Offer
Tip: Research the company's products and culture.
Global Market Intelligence & Relocation Insights
At JobSetuu, we specialize in helping talent navigate the global job market. Here is what you need to know about the current landscape in Global and beyond:
The demand for skilled professionals is increasingly borderless. For roles based in Global, understanding the local cost of living, visa requirements (if applicable), and cultural nuances is vital. If this is a remote role, consider the time zone alignment and the asynchronous communication culture of the hiring organization.
Relocation Support: Many forward-thinking companies offer relocation packages that include moving stipends, temporary housing, and legal assistance with work permits. When evaluating an offer, look beyond the base salary—consider the total compensation package, including equity, bonuses, and healthcare benefits.
Work-Life Balance Trends: Hybrid and remote work have become standard in many regions. Research the local labor laws and common practices regarding work hours and vacation time to ensure the role aligns with your lifestyle goals.
Leveraging JobSetuu's tools can help you compare salaries across different cities and understand the "purchasing power" of your potential offer, ensuring you make an informed decision for your long-term career path.
Skills & Competency Roadmap for Professional Development
To remain competitive in Professional Development, we recommend focusing on the following core competencies over the next 12-18 months:
- Technical Mastery: Deepen your expertise in the core tools and languages relevant to your field. For developers, this might be cloud architecture; for marketers, it might be data-driven attribution modeling.
- AI Augmentation: Learn how to leverage generative AI and automation tools to increase your productivity. Understanding how to integrate these technologies into your workflow is becoming a non-negotiable skill.
- Leadership & Strategy: Even in individual contributor roles, the ability to think strategically and lead projects from inception to completion is highly valued. Focus on stakeholder management and high-level project planning.
- Data Literacy: The ability to interpret data and use it to drive decisions is essential across all business functions. Familiarize yourself with data visualization and basic analytical concepts.
By investing in these areas, you not only prepare yourself for the role you are applying for today but also build a resilient foundation for the opportunities of tomorrow.
Apply via JobSetuu
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