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 Senior Forward Deployed Engineer. You don't just embed with clients. You run the engagement. You set the technical and delivery strategy. You make the customer successful. And you make the FDEs around you better.

A typical week might include:

Leading a discovery session with a client's VP of Operations, mapping the real workflow, not the documented one, and identifying where AI creates 10x impact
Architecting a multi-workstream deployment plan: which workflows to automate first, what data is required, what "done" looks like in measurable terms
Building an eval framework that proves the AI system works, not with vibes, but with acceptance criteria the client's team can verify
Unblocking an FDE who's stuck on a data integration problem, pairing in the CLI to debug, then turning the solution into a reusable pattern
Running an exec stakeholder review: showing progress in business terms (hours saved, error rates reduced, adoption metrics), not technical terms
Codifying a deployment pattern into a playbook so the next engagement at a similar client starts at 60%, not zero

This is not a management role. You still build. You still ship. You're in the CLI daily. But you also set direction, make architectural calls, and own the outcome of an entire engagement, not just a workstream.

This is not a solutions architect role. You don't draw diagrams and hand them off. You own discovery through production. When the deployment hits a wall at 2 AM, you're the one who finds the path through and documents it so no one else has to.

Yes, the market increasingly calls this "technical consulting," and that's a fair description. OpenAI, Google Cloud, and Salesforce are all standing up FDE teams that look a lot like this. The line we hold at ForgeVista is the one between recommend and implement: you own the system that ships into production and the adoption that follows it. There is no separate implementation partner picking up your deck.

The Profile

You're a business operator who became technically dangerous, and then kept going. You've been doing this long enough that you've seen what works and what doesn't. You've shipped AI solutions that real people use in production. You've learned through failure. You have opinions about what makes deployments succeed, and evidence to back them up.

You started in the business world: consulting, operations, analytics, delivery management. You understood workflows, stakeholders, and where documented processes drift from how the work actually happens, all before you understood code. Then AI arrived, and you didn't just learn it. You mastered it. You've been building and shipping with AI tools long enough that you've developed intuition for where AI creates real value and where it's theater.

You bring:

5-8 years of experience spanning business operations and AI-powered delivery
A track record of leading client engagements or deployments end-to-end, not just contributing to them
Deep CLI fluency: you live in the terminal, pair with AI agents daily, and build reproducible workflows by default
Proven ability to scope ambiguous problems, set acceptance criteria, and ship solutions that stick
Experience mentoring or leveling-up other team members (formally or informally)
Exec stakeholder presence: you can present to a C-suite in business language and debug a pipeline in the same afternoon

You've probably:

Led at least one engagement where you were the senior technical person in the room
Built systems that ran in production for months (not just demos that impressed in a meeting)
Developed your own frameworks or patterns for recurring deployment challenges
Learned the hard way that the biggest risk in any AI deployment isn't the technology. It's adoption

What matters is outcomes, not credentials. Can you show us an engagement you led? Can you walk us through a deployment that failed and what you'd do differently? Can you demonstrate that you make teams better, not just yourself?

What We Evaluate

We don't hire for titles or tenure. We hire for demonstrated leadership in AI deployment.

1. Deployment Track Record (AI Now)

Have you shipped AI systems that people actually use? We want to see production deployments, not prototypes. Show us what you built, how you measured success, and what happened after launch. Bonus: show us something that failed and how you recovered.

2. Technical Depth + CLI Mastery (CLI Native)

Can you architect a deployment, build the critical path yourself, and operate entirely in the CLI? We need someone who can drop into any part of the stack (data pipelines, agent workflows, eval frameworks, infrastructure) and be productive. Not expert in everything, but dangerous everywhere.

3. Engagement Leadership

Can you walk into a client organization, earn trust at every level (operators to executives), and drive an engagement to successful outcomes? This means scoping, prioritizing, saying no to the wrong things, and shipping the right things, without waiting for someone else to make the hard calls.

4. Team Multiplier

Do you make the people around you better? We're looking for someone who turns field learnings into reusable patterns, who mentors through pairing (not lecturing), and who raises the bar for what "shipped" means across the team.

5. High Agency

At this level, high agency is table stakes, but worth naming. You don't wait for permission to remove a blocker, escalate a risk, or rewrite a plan that's stopped working. You can push back hard on direction, then commit fully when the call is made. You raise the bar around you by example, not by edict.

We call this Founder Mode in our culture deck. At your level, it shows up less as "doing the work yourself" and more as making sure the right work gets done by the right person on the right timeline, without becoming a bottleneck.

6. Pod Architecture & Orchestration

Can you stand up a 90-day delivery pod for a client (strategist plus builders plus the AI agents you'll lean on) and pick the 1–2 highest-leverage use cases to ship from? The industry is converging on this pattern (Salesforce's FDE pods, OpenAI's Deployment Company, Google Cloud's customer transformation teams). Our distinction is that you don't hand the agent workflows off to a separate implementation team. You direct the agents inside the pod yourself, evaluate their output, and turn distributed intelligence into client decisions.

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 a case study or portfolio of an engagement you've led. Show us the work.

What We Offer

$180K–$250K base salary: competitive, benchmarked, paid regardless of outcomes
Sprint Point Velocity Incentives: tied directly to engagement outcomes, delivery quality, and team leverage. 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.
Engagement ownership: you run client deployments, not workstreams within them
Real AI work, every day: production deployments with frontier models, not strategy decks or readiness assessments
Team building: you'll shape how ForgeVista's FDE practice operates, not just execute within it
CLI-native tooling: we invest in the best AI agents and developer tools. You'll work with the frontier.
Client variety: different industries, different problems, constant learning. No two engagements are the same.
Remote-first. Travel depends on each client's preference. Fully remote clients = fully remote work. Senior engagements often start with an in-person kickoff, then 25–50% on-site for clients who prefer in-person collaboration. We work the way the client works.
Growth trajectory: the FDE practice is being built now. The path from Senior FDE to Director is real and short. Three tracks (IC, Manager, Executive) with real progression. See how we grow.

What This Isn't

It's not a role where someone else scopes the engagement and hands you a spec
It's not a role where you manage a team from a distance. You're in the work
It's not a role with a stable, well-documented playbook. You're writing the playbook
It's not a role for people who need every tool to be mature before they can be effective
It's not a role for people who optimize for consensus over outcomes

If you've been doing client-facing AI work and you're tired of organizations that move too slowly, ship too little, or mistake strategy for execution, we should talk.

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