Position Summary

What Makes This Role Different:

Portfolio-scale-leverage - A typical FDE makes one engineering org faster. At Vista, a system you prove at one company becomes a reusable accelerator across the next five. A playbook you write this quarter raises the baseline across 90+ companies. You are not optimizing one product. You are reshaping how enterprise software gets built across the category.

Vendor-agnostic and frontier-first - You are not implementing any one company's technology. Claude Code today, something else next quarter, and something else after that. The frontier moves every few months and Vista's playbooks move with it. You bring what actually works, not what a partner agreement requires.

Compounding technical currency -Few roles in the market sit this close to the frontier for this long, across this many real production environments. Your peer group is a bench of FDEs, architects, and strategists working the same hard problems in parallel. The role makes you sharper every quarter, by design.

This is a remote position, with travel to portfolio company sites as required by engagements. Travel is expected to range form 35% to 50%, depending on the engagement. The role is available for an immediate start.

Responsibilities

What You Will Do:

• 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.

What Success Looks Like:

• By month six, a strong FDE has:
• Shipped at least one engagement that measurably reduced KTLO burden or accelerated feature throughput, with metrics the company's engineering leadership signs off on.
• Left behind a working set of agentic workflows, evals, and tooling the company's engineers operate without external support.
• Contributed at least one reusable accelerator or playbook the next FDE engagement uses on day one.
• Built credibility with senior engineering leadership at the company, to the point of being requested back.

Qualifications

Required Experience:

• 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%.

Desired Experience:

• 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.

The annualized base pay range for this role is expected to be between $200,000 - $315,000. Actual base pay could vary based on factors including but not limited to experience, subject matter expertise, geographic location where work will be performed and the applicant's skill set. The base pay is just one component of the total compensation package for employees. Other components may include an annual cash bonus and a comprehensive benefits package.