Senior Software Engineer, NLP

GitLab · Bengaluru

Data & AI

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 Software Engineer, you'll build and deliver autonomous, agentic software development lifecycle capabilities for GitLab's engineering teams. You'll lead technical execution, mentor other engineers, and work closely with Product Managers, engineers, and AI and machine learning partners. You'll turn complex requirements into robust, secure, and performant AI-driven solutions, with a focus on high-quality code, reliable systems, measurable performance, and safe use of AI across the software development lifecycle.

What you’ll do

Build autonomous, agentic software development lifecycle features that support team goals and GitLab's product roadmap.
Develop and deploy AI agents that automate engineering tasks such as merge request authoring, test generation, and security remediation.
Collaborate with Product and AI and machine learning teams to break down complex requirements and deliver solutions iteratively.
Write clean, maintainable code and conduct thorough code reviews to support the quality and safety of agentic workflows.
Build and maintain orchestration patterns and safety guardrails for AI services.
Measure and improve the performance, latency, and correctness of AI-driven features using defined evaluation frameworks.
Participate in on-call rotations and debug complex issues involving AI services and autonomous agents.
Follow GitLab's security, compliance, and data governance standards while contributing to documentation, playbooks, reusable libraries, and the growth of other engineers.

What you’ll bring

Experience building and shipping production-grade software applications, including transferable experience from related engineering domains.
Experience with AI and machine learning application programming interfaces, large language models, or agentic frameworks in a web development context.
Proficiency in a modern programming language such as Ruby, Go, or Python, along with experience working with distributed systems.
Strong understanding of the software development lifecycle, continuous integration and continuous delivery, and developer tools.
Experience with testing frameworks, observability tools, and performance monitoring.
Ability to communicate technical concepts clearly and collaborate across functions.
Experience writing maintainable code, reviewing others' work, and supporting secure, reliable systems.
Ability to mentor junior and intermediate engineers and help them develop their technical skills and understanding of AI patterns.

About the team

We build agentic capabilities that improve how software is planned, developed, tested, secured, and maintained. We work with Product and AI and machine learning partners to deliver safe, reliable automation for our internal workflows and GitLab product features, while sharing reusable patterns and practical guidance across engineering.

How GitLab Supports Full-Time Employees

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.

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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.