Champ AI - Deployment Architect / Forward Deployed Engineer

Champ AI is building a multimodal work-agent orchestration platform that helps operations teams automate end-to-end workflows—not just "chat with docs." We're building agentic systems that can reliably take actions across tools (including browser and phone calls), handle real-world edge cases, and continuously improve with evaluations and feedback loops.

The Role

We're looking for a Deployment Architect / Forward Deployed Engineer to own the path from "first customer call" to "signed contract and live in production." You'll sit next to our customers, map their messiest workflows, stand up working agents in days (not quarters), and carry deals across the finish line.

This role is the rare combination of technical depth and deal-driving instinct. Your job is to take an interested prospect through the POC stage and turn them into a paying customer. That means configuring real agents against real customer data on Monday, then running the pricing conversation on Friday—and knowing how each one shapes the other. Pure engineers stall in procurement; pure sellers can't get the POC working. You do both.

This is the highest-leverage role on the team right now. Every pilot you land becomes a product signal, a reference customer, and a revenue line. Every deal you lose tells us what to build next. The company moves at the speed you move at.

If you're technical (or "leaning technical") and want direct, unfiltered exposure to real customers—their pain, their politics, their budgets, their buying process—this is one of the best seats in the building for it. It's also one of the best possible preparations for starting your own company: you'll see how enterprises actually buy, how pilots actually die, and how trust actually gets built.

You'll likely own several of these areas end-to-end:

Customer discovery solutioning

• Sit in on (and often run) first calls with operations leaders. Translate vague pain into a crisp, scoped workflow we can automate.

• Shadow real operators doing real work—on Zoom, in their tools, in their SOPs—so we build for the job, not the pitch deck.

• Translate what you hear into working demos, POCs, and pilot plans that get champions fired up and skeptics nodding.

Pilot delivery deployment

• Stand up agents against live customer data and real tools within the first week of a pilot. Speed is the product.

• Configure prompts, tools, evals, and guardrails for each customer's quirks; know when to hand off to product engineering vs. when to solve it yourself.

• Own the pilot success plan: what metric we're moving, what "good" looks like, who on the customer side signs off, and by when.

Deal execution

• Drive deals forward with a sense of urgency. Nudge, don't nag. Create momentum without creating friction.

• Read the room: identify the champion, the economic buyer, the blocker, and the quietly-skeptical engineer. Build a plan for each.

• Own the close: pricing conversations, security review, procurement, redlines. Know which concessions are cheap and which are expensive.

• Write the follow-ups that actually get replied to. Summaries, next steps, mutual action plans—short, specific, dated.

Product feedback loop

• Be the highest-signal source of customer truth inside the company. Ship back structured, ranked feedback—not anecdotes.

• Partner with engineering on what to harden next: the five things breaking across pilots, not the one thing breaking for one customer.

• Build the reusable pieces: demo environments, pilot templates, onboarding flows, solution patterns. Leverage your own wins.

Trust expansion

• Be the face of Champ AI for evaluators. Calm under pressure, credible on technical detail, honest about limitations.

• Turn pilots into multi-team and multi-workflow expansions. The second deal inside an account is where the real business is.

We expect at least 1–2 years of experience in a similar customer-facing, deal-carrying technical role (Forward Deployed Engineer, Deployment Strategist, Solutions Architect, Solutions Engineer, Applied AI, or equivalent). We especially want to hear from:

• Ex-founders. You've built and sold something, even if it didn't fully work. You know what it feels like to own a pipeline.

• Alumni of AI-native companies. You've done this work at places like OpenAI, Anthropic, Scale, Glean, Harvey, Sierra, Decagon, Hebbia, Cresta, Writer, Cognition, or similar. You understand what "good" looks like at an AI-native company—and what doesn't translate.

You have real "in the room with customers" scars. Concretely:

• You've carried pilots or deals from first call to production at a technical startup, or

• You've owned solution engineering that takes a customer through the full technical arc — scoping the POC, standing it up in their environment, debugging in real time, and delivering real results in production.

You likely have:

• Technical range. You can read a codebase, write a Python script, debug an LLM prompt, sketch an integration, and hold your own with a skeptical engineer. You don't need to be the best engineer in the room—you need to be credible, fast, and unafraid.

• Deal instinct. You treat every open deal as a living thing. You know the next step, the risk, and the timeline, and you don't wait to be asked. You push without being pushy.

• Client dynamics fluency. You pick up on who's actually deciding, whose ego is in play, who needs a win, and who's trying to kill the project. You plan around it.

• Urgency as a default. You answer fast, follow up same-day, and treat "Monday" as "Monday morning." You compress cycles everyone else lets drift.

• Systems thinking under ambiguity. You can scope a messy workflow into a two-week pilot and know what to cut. You can tell a demo bug from a product bug.

• Clear writing. Follow-ups, mutual action plans, pilot reports, internal debriefs—short, specific, skimmable.