Applied AI Engineer

Emberline

2d•Remote

About The Position

Emberline is a two-partner investment firm that buys and builds founder-led businesses. We're operators at heart. We don't buy companies to financial-engineer them; we buy them because we believe hands-on support can make a real difference. That means embedding alongside management, building infrastructure, and doing the unglamorous work that turns good businesses into great ones. We have three portfolio companies today and are building toward five. You'll be part of a tight core team, but your day-to-day reaches across those companies and the operators, finance leaders, and advisors who support them. We're looking for an Applied AI Engineer to drive AI implementation across our portfolio companies. This is a new role, and frankly, a new function. You won't find a playbook for this job because it doesn't exist yet. Your mandate: make sure our portfolio companies are actually using AI. Not talking about it, not "exploring" it, but deploying it in ways that move the needle. That means customer service automation, developer productivity tools, sales and marketing workflows, back-office operations, and whatever else makes sense. You'll work closely with the Managing Partner to identify opportunities, evaluate tools, and get things live. Then you'll train portco teams to own what you've built. Rinse, repeat, across every company in the portfolio. This is 80% hands-on implementation, 20% evaluation and planning. There's no playbook for this yet, at Emberline or anywhere else. The partners will be genuine thought partners as you build the function. The expectation is not that you arrive with everything figured out; it's that you're willing to figure it out alongside us. This is a high agency, high opportunity seat with the ceiling set by you.

Requirements

Experience in Product Management, Solutions Engineering, Technical Operations, or similar roles where you shipped things that required both technical and business judgment.
Hands-on experience with AI/ML tools in a professional context, whether that's deploying chatbots, integrating LLM APIs, building automation workflows, or similar. We care about what you've actually done, not credentials.
Strong understanding of APIs, integrations, and how systems connect. You don't need to be a software engineer, but you need to be able to read API docs and understand what's possible.
Excellent communication skills. You'll be explaining technical concepts to non-technical operators and translating business needs into technical requirements.
Comfort with ambiguity. This role doesn't have a playbook. You'll figure it out as you go.
This is a remote role but on-site engagements, rapport building and investigations are a key requirement, which will require travel.

Responsibilities

AI Implementation
Operational Audits: Assess each portfolio company's workflows across customer service, sales, marketing, finance, and operations, then identify where AI can reduce friction, cut costs, or improve quality.
Tool Deployment: Configure and deploy AI tools (chatbots, copilots, automation platforms, etc.) across portco functions. You're not building from scratch; you're pulling best-in-class tools off the shelf and making them work.
Workflow Integration: Connect AI tools to existing systems like CRMs, helpdesks, marketing platforms, and codebases. You need to understand APIs, integrations, and how data flows between systems.
Rapid Prototyping: Test new AI applications quickly. Prove value in days or weeks, not months. Kill what doesn't work; scale what does.
Vendor & Tool Evaluation
Landscape Monitoring: Stay current on AI tooling: what's shipping, what's vaporware, what's actually production-ready. The space moves fast; you need to move with it.
Vendor Screening: Evaluate vendors, run trials, negotiate pricing. You're the filter between hype and reality.
Build vs. Buy Decisions: Know when to use off-the-shelf tools, when to customize, and when to build something custom.
Enablement & Knowledge Transfer
Team Training: Train portfolio compay teams to use and maintain the tools you deploy. The goal is handoff, not dependency.
Documentation: Build simple, usable guides for each implementation. When you move on, the portco team should be able to run it themselves.
Cross-Portfolio Learning: What works at one portfolio company should benefit the others. Build repeatable playbooks.
Partner Support
Weekly Syncs: Work closely with the Managing Partner to prioritize, troubleshoot, and align on roadmap.
Experimentation Partner: Test new tools and approaches alongside the Partner. Be the person who's already tried it when the Partner asks, "What about X?"