Engineering Manager, Forward-Deployed Engineering

GrowthX AI

7d•Remote

About The Position

AI is reshaping go-to-market. Not just content creation. The entire surface area: product experiences, developer tools, documentation, integrations, research systems. GrowthX runs a high-end AI product studio for this shift. We build AI agents, custom products, and advanced automations for B2B companies on top of Output.ai, our open-source AI workflow framework. Think Palantir's forward-deployed model, but for GTM. Recent examples: For Lovable: An AI agent that creates templates for their product For Airbyte: An agent that integrates with new connectors and creates docs pages by sending pull requests For Augment: An entire research site for discovering and cataloging MCPs This is AI + product development + GTM. We have a team of 5 today. We're growing to ~20. We need someone to lead this expansion.

Requirements

Technical leader who still codes. You can architect AI agents, debug production issues, and review PRs. You're hands-on when it matters. You're not looking for a role where you just manage people and attend meetings.
Product thinker. You don't just build what's asked. You understand the client's problem, propose solutions, and ship products that work. You think about UX, not just architecture.
Experienced people manager. You've built and led engineering teams before. You know how to hire well, give direct feedback, and terminate team members when needed. You've navigated the messy parts of team building.
Client-facing capable. You can sit in a strategy call, understand what the client actually needs, and translate that into a project. You're comfortable with ambiguity and client expectations.
AI-native. You've built with LLMs. You understand prompting, context windows, agent architectures, and the current state of what works and what doesn't. This isn't theoretical for you.
High bar on output quality. AI can generate a lot of code fast — that makes reviewing it more important, not less. You read what it produces, understand it, refactor it, and don't merge output you wouldn't defend in a review. You QA your own work manually before it reaches anyone else.
Pragmatic over perfect. You ship working solutions and iterate based on real usage. You don't over-engineer. You solve the problem in front of you.
Excellent communicator. Writing and verbal. You can explain technical decisions to non-technical people. You document well. You run effective meetings.

Nice To Haves

Led forward-deployed or professional services engineering teams before
Built production AI agents or LLM systems
Shipped products end-to-end (not just features within a product)
Experience in developer tools, GTM tech, or B2B SaaS
Contributed to or maintained open-source projects
Agency or consulting background with high-touch client delivery

Responsibilities

Team Leadership. Build a team of AI-native forward-deployed engineers and designers. Set technical standards. Run effective 1:1s, invest in each engineer's growth, and give direct feedback. Build a team that clients trust and engineers want to join.
Technical Direction. Define architecture patterns for AI agents and client products. Review code. Make build vs. buy decisions. Push the boundaries of what's possible with Output.ai.
Client Delivery. Ensure the team ships excellent work. Scope technical feasibility early with the sales team. Jump in on complex projects. Solve the hard problems when they come up.
Platform Building. Turn client projects into reusable capabilities. An agent pattern built for one client becomes a template for the next. A custom integration becomes a module in Output.ai. Each engagement should make the next one faster and better. The goal is compounding leverage.
Operations. Run prioritization cycles. Allocate capacity across client pods. Balance urgent client requests with system improvements.