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Forward Deployed Engineer

Embed with clients. Translate messy business problems into AI-powered solutions. Ship them.

Employment:
Full-Time
Location:
Remote-first (US)
Travel:
Client-dependent — fully remote to 25-50% on-site
Compensation:
$120K–$180K + Sprint Point Velocity Incentives

L1 · FDE

$120K–$180K

+ Sprint Point Velocity Incentives

Employment:
Full-Time
Location:
Remote-first (US)
Travel:
Client-dependent — fully remote to 25-50% on-site
Apply for this role

Time allocation

Rough mix across the role. Every engagement varies.

Discovery 10%Client success 5%Innovation 15%Admin 5%Delivery 65%Delivery65%Discovery 10%Client success 5%Innovation 15%Admin 5%
0%: Talent dev, Business dev100%

About ForgeVista

We deploy AI into the real world. Not slide decks. Not proofs of concept. Production systems that change how businesses operate. Our team embeds directly with clients to build, ship, and scale AI solutions, and we do it at startup speed with enterprise quality.

Three things define how we work: AI Now (we ship with AI daily, not "someday"), CLI Native (the terminal is our cockpit, every role, every person), and High Agency (you own the outcome and move without waiting for permission).

Before you apply, please read our culture deck. Our culture isn't aspirational. It's how we actually operate. If it doesn't resonate, this probably isn't the right fit. We'd rather you self-select than discover the mismatch after a few interviews.


The Role

You're a Forward Deployed Engineer. You embed with clients. You translate their messy business problems into AI-powered solutions. And you ship them.

A typical week might include:

  • Sitting in a client's operations room, watching how they actually work, not how the org chart says they work
  • Mapping a manual workflow and designing an AI-native replacement that runs in production, not PowerPoint
  • Building a prototype in the CLI using AI agents, testing it against real data, iterating with the client team
  • Running eval loops to prove your solution actually works, not just feels like it works
  • Pushing code that automates something a team of three used to do manually
  • Writing a concise playbook so the next deployment at a similar client doesn't start from scratch

This is not a consulting role. You don't write recommendations. You write code, build workflows, and ship systems. You're not an observer. You're in the trenches.

This is not a traditional engineering role. You don't sit in a product team building features for millions of users. You sit with one client and solve their specific problems. You're as comfortable scoping requirements as you are debugging a pipeline.


The Profile

Most of our team started in business and got technical through AI: operators and BAs who automated their own work and didn't stop. If that's you, you'll feel at home fast.

If you came in from the engineering side and learned the business through real shipping, you're welcome here too. The bar is the same either way: did you ship, do you live in the CLI, can you sit with a client and see where the leverage is?

If you started in the business world (consulting, operations, analytics, project management), you understood workflows, stakeholders, and where documented processes drift from how the work actually happens. Then AI arrived, and you went deep. Not surface-level deep. Actually deep. You automated your own work. You built tools. You paired with AI agents. You got comfortable in the terminal because that's where the real power is. You can't imagine going back.

You might have:

  • 2-5 years of experience in business analysis, consulting, operations, or similar
  • Built and shipped something with AI tools: an automation, a workflow, a prototype that people actually used
  • Gotten CLI-comfortable through AI tools (Claude Code, Codex, Gemini, or raw terminal work)
  • Demonstrated BA instincts: you can walk into a room, understand a process, and find where it breaks
  • Experience working directly with clients or stakeholders (not just internal teams)

You probably haven't (and that's fine):

  • Studied computer science formally
  • Written production code at scale before AI tools
  • Worked at a tech company
  • Called yourself an "engineer" before

What matters is proof, not pedigree. Can you show us something you've built with AI? Can you navigate a terminal without panic? Can you sit with a client, see the system behind their request (the workflow, the constraints, the stakeholders), and frame the problem in a way the room agrees with?


What We Evaluate

We don't hire for credentials. We hire for evidence.

1. AI Immersion (AI Now)

Have you gone deep? We're looking for obsessive exploration: the person who spent a weekend automating their entire reporting workflow, who built an AI agent to handle a task that was consuming 10 hours a week, who can't stop tinkering.

2. CLI Comfort (CLI Native)

Can you operate in a terminal? We don't need you to write bash scripts from memory. We need you to be able to navigate, search, run commands, use git, and pair with AI agents in the CLI without freezing.

3. High Agency

You see the bottleneck and start moving it forward, no waiting for permission. You walk into an unfamiliar business, find what's broken, and prioritize what to fix. You proactively remove blockers, technical and human. You can disagree hard, then commit fully.

We call this Founder Mode in our culture deck. The idea: when every team member operates with this much agency, the founder can stay focused on direction and scale instead of getting pulled into every decision. Your high agency is what makes that possible.


How to Apply

Eligibility: This role is open to candidates based in the United States who are authorized to work in the US. We are not sponsoring work visas or considering applicants located outside the US at this time.

Apply through the link below. We evaluate artifacts before resumes. When you apply, you'll be asked to share something you've built with AI. A repo, a Loom, a writeup. Show us the work.


What We Offer

  • $120K–$180K base salary: competitive, benchmarked, paid regardless of outcomes
  • Sprint Point Velocity Incentives: tied directly to deployment impact, delivery quality, and playbook contribution. Our model rewards throughput and excellence, with high-performers earning significantly above base.
  • Cash-focused compensation: we prioritize high liquidity and clear performance rewards over long-term equity locks for this role.
  • Health + development benefits: health, dental, and vision coverage, plus a professional development budget for learning, conferences, and the tools you need to stay sharp.
  • Real AI work: not "AI strategy" or "AI readiness." Production deployments, every week.
  • Growth trajectory: you're joining at the ground level of a new AI deployment practice. The ladder is short and the ceiling is high. Three tracks (IC, Manager, Executive) with real progression. See how we grow.
  • CLI-native tooling: we invest in the best AI agents and developer tools. You'll work with the frontier.
  • Client variety: you won't be stuck on one project for years. Different clients, different problems, constant learning.
  • Remote-first. Travel depends on each client's preference. Fully remote clients = fully remote work. Clients who prefer or require on-site engagement = typically 25–50% on-site with heavy remote integration between trips. We work the way the client works.

What This Isn't

  • It's not a job where you'll write reports and hand them to someone else to implement
  • It's not a job with detailed specs and daily standups
  • It's not a job where you'll wait for the "right tool" before starting
  • It's not a job for people who think AI is hype, a threat, or "not ready"

If you read this and felt excited, not worried, we should talk.


ForgeVista is an equal opportunity employer. We evaluate candidates based on demonstrated ability and proven immersion, not pedigree or credentials.

Skills + tools

Filled area = hire-bar (day-1 expectation). Scale: 1 = exposure, 5 = mastery. Same axes across all ForgeVista roles so you can compare. The dashed axis is something we deliberately don't do.

12345AI-NativeDevelopmentLLM ApplicationEngineeringEnterprise AgentEngineeringAgentic SystemsEngineeringDataEngineeringAnalyticsEngineeringBusiness Analysis& DiscoveryChange Management& Client SuccessSolution & PlatformArchitectureIdentity, Security& IT SystemsML Research &Model Training
Hire-bar (expected day 1)We don't do this