Senior AI Engineer

GitLab

Confirmed live yesterday High trust

Remote

Quick summary

Work type: Remote
Location: Remote
Salary: $108,400–$129,600 / yr
Posted: 105 days ago
Freshness: Confirmed live yesterday

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $204k

This role $119k

$91k most similar roles pay here $270k

This role pays less than 98% of similar roles. Most pay $162,000–$246,150 — the shaded band above. At the midpoint, this role pays about $119k versus about $204k for comparable roles.

Based on 240 similar postings.

Employer

About GitLab

GitLab is an all-remote software company that develops an AI-powered DevSecOps platform combining source code management, CI/CD, security scanning, and project planning in a single application.

GitLab currently has 79 open roles on FindRole.

Listed pay typically runs $137,400–$213,600 across 61 roles with salary data.

Most-posted roles

View all roles at GitLab

At a glance

TL;DR · Senior AI Engineer

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As a Senior AI Engineer on the Enterprise Technology & AI team, you will serve as a technical leader building internal AI-powered solutions to drive measurable business outcomes across Sales, Marketing, and Customer Support. You will own initiatives from discovery through deployment, diagnosing business problems by mapping workflows and identifying constraints before developing prototypes. Your daily work involves integrating AI capabilities into existing systems using APIs, orchestration tools, and the GitLab Duo Agent Platform. Key technical requirements include proficiency in Python or TypeScript, experience with REST APIs and GraphQL, and deep expertise in prompt engineering, agentic architecture patterns, and model selection. You will navigate the LLM ecosystem including Anthropic and OpenAI models while ensuring AI safety through robust guardrails. The role requires systems thinking to improve organizational flow and resolve bottlenecks within enterprise business systems like Salesforce and Zendesk.

What does a AI Engineer earn?

Median $211200 from 132 postings across 36 companies.

See salary data

Skills

Python JavaScript TypeScript LLM Prompt Engineering RAG REST API GraphQL GitLab CI/CD Anthropic OpenAI Salesforce Marketo Zendesk Workato n8n Make Relevance AI Glean

What you'll do

Diagnose business problems by mapping workflows and identifying constraints before determining if AI is the appropriate solution.
Own AI initiatives end-to-end from initial stakeholder discovery and technical design through implementation and deployment.
Develop and ship functional AI prototypes quickly to deliver measurable business value and improve organizational flow.
Integrate AI capabilities into existing systems using APIs, orchestration tools, and modern AI platforms like GitLab Duo.
Act as "Customer Zero" by utilizing and showcasing GitLab's internal AI offerings to provide feedback to R&D.
Partner with cross-functional stakeholders to bridge technical and non-technical perspectives while aligning on specific outcomes.
Define and track success using business metrics, flow metrics, and feedback loops to ensure measurable impact.
Contribute to the team's technical direction by evaluating tools and creating reusable documentation for scaling impact.

What we're looking for

Proficiency in at least one modern scripting language such as Python, JavaScript, or TypeScript.
Strong understanding of REST APIs, GraphQL, and integration patterns.
Deep experience with prompt engineering, including system prompts, context management, and iterative design.
Expertise in agentic architecture patterns, including tool use, multi-agent orchestration, and guardrails.
Ability to make informed decisions on model selection, cost-performance trade-offs, and RAG architectures.
Experience building production-grade AI solutions with a focus on safety, risk awareness, and data leakage prevention.
Familiarity with enterprise business systems including CRM (Salesforce), marketing automation (Marketo), and support platforms (Zendesk).
Experience with GitLab platform and CI/CD workflows (preferred); experience with low-code tools like n8n or Make (preferred).