Senior Professional Services, Forward Deploy Engineer

GitLab

37d•Remote

About The Position

As a Senior Professional Services Forward Deploy Engineer at GitLab, you'll be an embedded GitLab Duo Agent Platform expert who helps customers move from ideas to production. You'll work directly with customer teams as a consultative partner, running in-depth discovery to understand their environment and priorities, then designing and delivering solutions that connect business goals to architecture and implementation. This is a deeply technical, customer-facing role where you'll build and deploy Custom Agents, Custom Flows, and CI/CD integrations. You'll own delivery end-to-end, from prototype through production support. You'll partner closely with Professional Services and Customer Success stakeholders, including Professional Services Engineers, Project Managers, Customer Success Managers, and Solution Architects. You'll also measure and communicate impact using customer-aligned success criteria and analytics, and you'll help codify repeatable deployment patterns and lessons learned into reusable assets and product feedback. This role reports to the Senior Manager, Technical Architects, and you'll travel for customer site engagements and company onsite events. Some examples of our projects Leading customer discovery and defining a prioritized GitLab Duo Agent Platform use case roadmap tied to clear success criteria Designing and delivering production-ready GitLab Duo Agent Platform implementations, including Custom Agents, Custom Flows, and CI/CD integrations Building rapid prototypes to demonstrate the art of the possible with agentic AI and iterating based on customer feedback Integrating the GitLab Duo Agent Platform with customer systems and workflows using GitLab APIs, pipeline configuration, and infrastructure as code Establishing AI governance and security controls (for example, role-based access control, model selection policies, and enterprise compliance requirements) Measuring and communicating impact using DORA (DevOps Research and Assessment) metrics, AI Impact Analytics dashboards, and Value Stream Analytics, then translating what we learn into reusable patterns and product feedback What you'll do 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.

Responsibilities

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.