Senior Forward Deployed Engineer

Vista Equity Partners is a leading global investment firm that invests in enterprise software and technology-enabled organizations. They are hiring Senior Forward Deployed Engineers to embed within the engineering teams of their portfolio companies, focusing on delivering production outcomes and enhancing engineering capabilities across multiple organizations.

Responsibilities:

• Embed with company engineering teams for focused 8 to 24 week engagements. Own delivery end to end
• Work inside their repos, CI/CD, security review, and code standards. Leave behind systems their teams can operate, extend, and trust
• Build advanced CodeGen and agentic workflows including custom subagents, skills, MCP servers, eval harnesses, background agents, and PR review automation. Implement evals, guardrails, observability, and human-in-the-loop checkpoints sized to risk
• Pair program and prompt alongside their engineers as a teaching mechanism, not a ghostwriting mechanism. Success is their team operating these patterns without you
• Partner with engineering leadership to scope high-leverage opportunities with clear business metrics and acceptance criteria
• Contribute patterns, accelerators, and reference implementations back to Vista's shared FDE and AI Ops playbooks for reuse across the portfolio

Requirements:

• 7 to 10 years of production software engineering experience, with a track record of shipping real systems at real scale
• 3+ years of sustained, daily use of frontier AI tools (Claude Code, Cursor, Copilot, Devin, or equivalent) on production work, with demonstrated advanced use: custom agents, skills, MCP servers, eval harnesses, autonomous workflows, or multi-repo refactors
• Demonstrated success driving AI or automation transformation at the enterprise level, ideally across multiple organizations
• Comfort ramping quickly across languages and stacks (Python, Java, Go, TypeScript, C#, and others) based on the company you are embedded in
• Cloud infrastructure depth on AWS, Azure, or GCP, plus containerization, CI/CD, and observability
• Prior FDE, embedded solutions engineering, technical consulting, staff product engineering, or early-stage startup engineering experience
• Willingness to travel 35% to 50%
• Built and operated agentic products in a commercial setting
• Led AI transformation inside an AI-native startup
• Built internal developer platforms or engineering productivity tooling that measurably changed how engineers worked
• Worked across multiple companies or clients in private equity, consulting, or solutions-engineering contexts
• Open-source contributions to AI tooling, evals, or developer-productivity projects