Software Engineer (full-stack), Gtm Tooling

Cockroach Labs Cockroach Labs · Data AI · United States · Remote · Sales

Fullstack Software Engineer to join the GTM Engineering team, focusing on building internal knowledge and intelligence infrastructure. This role involves creating a new system that combines agentic execution with software development fundamentals to drive improvements across the company. The engineer will define and build a modern, mixed classic-and-agentic workflow system enabling seamless human-AI agent collaboration, with a focus on UX, customer partnership, enablement, and observability.

What you'd actually do

  1. Design, implement, and maintain new features and integrations that enhance the GTM OS, our new system for delivering actionable intelligence across the company. This work will include both traditional and agentic engineering approaches, leveraging the latest AI technologies to build impactful tools and workflows.
  2. Design and build a next-generation workflow system with an interface optimized for seamless collaboration between users and AI agents. Delivering an intuitive and effective agent-assisted experience is critical to the success of the GTM OS platform.
  3. Partner directly with internal teams to understand how they spend their time and identify opportunities where we can better support them. In some cases, this may involve building entirely new features; in others, it may mean making iterative improvements to existing systems and workflows.
  4. Present and consult across Cockroach Labs to showcase the work we’ve built and help teams understand how to best leverage it. This includes presentations, detailed documentation, and workshops.
  5. Design intuitive, actionable observability tools that provide clear monitoring and alerting for continuously running workflow processing systems.

Skills

Required

  • 5+ years of hands-on software engineering experience
  • Comfort implementing graphical user interfaces using technologies like HTMX or React
  • Working knowledge of CI/CD pipelines, version control (Git), and Infrastructure as Code (Terraform, Ansible, etc.)
  • Experience working with at least one major public cloud provider (AWS, GCP, or Azure)
  • Understanding of SQL and relational database fundamentals, including schema design and query optimization
  • Proven ability to diagnose and resolve complex technical issues in production environments
  • Strong written and verbal communication skills, capable of tailoring information to both technical and non-technical audiences
  • Experience designing and managing data pipelines for AI systems, including ETL for LLMs, vector databases, or feature stores
  • A track record of designing and building AI-powered systems, tools, or infrastructure that others use — not just for your own productivity
  • A builder's instinct for reuse and extensibility. Your output becomes a platform, pattern, or capability others depend on
  • Clear judgment about where AI should be deeply integrated and where traditional approaches are more reliable

Nice to have

  • distributed systems or complex infrastructure projects, with a focus on the UX
  • Previous experience with distributed databases or high-availability systems is a plus
  • Enthusiasm for staying up-to-date with emerging technologies and incorporating them into new or existing solutions
  • Openness to giving and receiving feedback, with a mindset of continuous improvement
  • Willingness to adapt to changing priorities in a fast-paced, innovative environment

What the JD emphasized

  • agentic execution
  • agentic engineering
  • AI agents
  • agent-assisted experience
  • AI-powered systems
  • agentic workflows

Other signals

  • building internal knowledge and intelligence infrastructure
  • combine the latest advances in agentic execution with deep software development fundamentals
  • define what a modern, mixed classic-and-agentic workflow system looks like
  • humans and AI agents collaborate seamlessly
  • design and build a next-generation workflow system with an interface optimized for seamless collaboration between users and AI agents
  • design and building AI-powered systems, tools, or infrastructure that others use