Senior Technical Architect – AI

Role Overview

• Conduct deep customer discovery to understand business goals, technical constraints, and organizational dynamics, and translate them into clear problem statements and a prioritized use case plan for GitLab Duo Agent Platform.
• Partner with customer stakeholders across engineering, security, compliance, and business teams to align on success criteria, milestones, and adoption strategy for AI workflows in production.
• Design, build, and deploy production-ready GitLab Duo Agent Platform solutions, including Custom Agents, Custom Flows, and CI/CD integrations that map to validated customer use cases.
• Embed with customer engineering teams to deliver hands-on implementations end-to-end, from prototype to production rollout, troubleshooting, and optimization.
• Configure and integrate platform foundations such as runners, network access, runtime sandboxing, GitLab APIs (REST and GraphQL), and AI governance controls (for example, role-based access control and model policies) to meet enterprise requirements.
• Measure and communicate impact using DORA (DevOps Research and Assessment) metrics, AI Impact Analytics, and Value Stream Analytics, and use those insights to guide iteration and expansion of successful use cases.
• Codify repeatable deployment patterns, reusable assets, and lessons learned, contributing back to GitLab through documentation, accelerators, and product feedback informed by field experience.
• Travel up to 50% for customer site engagements and company onsite events to support delivery, onboarding, and stakeholder alignment.

Requirements

• Demonstrated experience leading customer-facing technical engagements, from discovery through production rollout, with ownership of outcomes.
• Proficiency in Python, with experience building and operating production-grade applications and integrations.
• Experience delivering with GitLab CI/CD, including pipeline design, YAML configuration, and using GitLab APIs (REST and GraphQL).
• Hands-on experience with infrastructure as code (for example, Terraform or Ansible) and deploying solutions into enterprise environments.
• Working knowledge of large language model (LLM) capabilities and limitations, including prompt engineering and building agentic workflows (such as Custom Agents and Custom Flows).
• Experience with Docker, container orchestration concepts, and runner configuration in secure environments.
• Familiarity with DevSecOps practices, including security controls, access management, and compliance requirements that impact deployment design.
• Strong written and verbal communication skills, with the ability to partner closely with customer stakeholders and translate business goals into technical plans in a remote, asynchronous environment.

Tech Stack

• Ansible
• Docker
• GraphQL
• Python
• Terraform

Benefits

• 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