Forward Deployed Engineer

Responsibilities

• Design and build agentic systems using models, tools, action loops, orchestration, context, retrieval, state, memory, evaluation, tracing, and human oversight.
• Develop context and knowledge systems using retrieval-augmented generation, cache-augmented generation, graph-based retrieval, repository understanding, and context optimization.
• Work directly with strategic customers to understand technical friction and turn ambiguous needs into working solutions.
• Build agent workflows, integrations, evaluation suites, reference architectures, and product capabilities.
• Contribute production-quality changes across GitLab Duo Agent Platform and the broader GitLab product.
• Evaluate and improve system quality, reliability, latency, cost, token use, safety, authorization, governance, and developer experience.
• Diagnose failures across models, context, retrieval, tool use, control flow, product behavior, permissions, and software-development workflows.
• Partner with Product and Engineering, generalize customer learning into reusable capabilities, and provide Staff-level technical leadership through architecture, implementation, review, mentorship, and cross-team influence.

Requirements

• Staff-level software-engineering experience building, shipping, and improving complex production systems.
• Hands-on experience designing and building substantive AI systems, including evaluating, tracing, debugging, and optimizing their behavior.
• Strong understanding of models, context, retrieval, tools, state, control flow, evaluation, and human oversight in agentic systems.
• Depth in one or more areas such as agent systems, context and knowledge systems, AI developer tools, inference, or AI-enabled product engineering.
• Strong programming skills in Python, TypeScript, Go, Rust, Java, Kotlin, Ruby, C#, or another relevant language.
• Ability to contribute across large, mature, polyglot codebases.
• Practical understanding of AI safety, authorization, governance, observability, and cost management.
• Ability to communicate clearly with customers and senior stakeholders, work through ambiguity, and build trust while remaining deeply technical.
• Record of Staff-level impact through technical direction, reusable systems, mentorship, cross-team influence, or product architecture.

Nice to Have

• Experience working with customers, design partners, or external engineering teams.
• Experience building AI systems for software development, coding agents, IDEs, code understanding, code review, testing, CI/CD, security, or incident response.
• Experience with LangChain, LangGraph, RAG, cache-augmented generation, knowledge graphs, agent evaluation, or tracing.
• Experience evaluating model and inference behavior and its effect on application or agent performance.
• Experience with self-hosted models, restricted environments, enterprise governance, or customer-controlled inference.
• Familiarity with Git, GitLab, CI/CD, developer platforms, or large open-source products.
• Experience with Ruby on Rails or GitLab’s existing product stack.
• Experience with AWS, Google Cloud, Azure, or Kubernetes.
• Experience with Infrastructure as Code tools such as Terraform or Ansible.
• Public technical writing, architecture guidance, open-source contributions, talks, or other evidence of technical leadership.

Compensation and Benefits

• Benefits supporting health, finances, and well-being.
• Flexible paid time off.
• Team Member Resource Groups.
• Equity compensation and Employee Stock Purchase Plan.
• Growth and Development Fund.
• Parental leave.