Forward Deployed Engineer, AI and Agentic SDLC

GitLab

Confirmed live yesterday High trust

Remote

Quick summary

Work type: Remote
Location: Remote
Posted: 128 days ago
Freshness: Confirmed live yesterday

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Salary context

How this pay compares to similar roles

Similar $204k

$148k most similar roles pay here $268k

This listing doesn't post a salary. Most similar roles pay $162,600–$246,150.

Based on 240 similar postings.

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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.

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At a glance

TL;DR · Forward Deployed Engineer, AI and Agentic SDLC

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As a Staff Forward Deployed Engineer, AI and Agentic SDLC, you will join the Forward Deployed Engineering team to bridge the gap between strategic customer needs and product delivery. You will work directly with customers to resolve technical friction by designing and building agent workflows, context systems, and integration points within the GitLab Duo Agent Platform. Your daily responsibilities include developing retrieval-augmented generation and graph-based retrieval systems, evaluating model behavior, and contributing production-quality code across the platform's CLI, IDE integrations, and AI Gateway. You will utilize a polyglot stack including Python, TypeScript, Go, Rust, Java, Kotlin, or Ruby to build robust agentic systems. The role focuses on solving complex problems in agentic software development by optimizing for reliability, latency, cost, and safety while translating ambiguous customer requirements into reusable platform capabilities and technical guidance.

What does a Forward Deployed Engineer earn?

Median $215000 from 45 postings across 23 companies.

See salary data

Skills

AI Engineering RAG LangChain LangGraph Python TypeScript Go Rust Ruby on Rails GitLab Git CI/CD Kubernetes Terraform Ansible AWS GCP Azure Knowledge Graphs Infrastructure as Code

What you'll do

Design and build agentic systems using models, tools, action loops, orchestration, and human oversight.
Develop context and knowledge systems using RAG, graph-based retrieval, and other optimization techniques.
Work directly in customer environments to translate ambiguous needs into functional technical solutions.
Build agent workflows, integration suites, and reference architectures to improve customer outcomes.
Contribute production-quality code across the GitLab Duo Agent Platform and broader product areas.
Evaluate and optimize system performance regarding reliability, latency, cost, safety, and developer experience.
Diagnose failures across models, retrieval systems, tool usage, and software development workflows.
Translate customer-specific learnings into reusable platform capabilities and technical guidance for the engineering team.

What we're looking for

Staff-level software engineering experience building and shipping complex production systems.
Hands-on experience designing, evaluating, tracing, debugging, and optimizing substantive AI systems.
Strong understanding of agentic systems including models, context, retrieval, tools, state, control flow, evaluation, and human oversight.
Proficiency in programming languages such as Python, TypeScript, Go, Rust, Java, Kotlin, Ruby, or C#.
Ability to communicate with customers and stakeholders while navigating ambiguity and maintaining technical depth.
Proven record of Staff-level impact through technical direction, mentorship, cross-team influence, or product architecture.
Experience working directly with customers, design partners, or external engineering teams (preferred).
Experience with LangChain, LangGraph, RAG, knowledge graphs, or other AI evaluation and tracing systems (preferred).