[Hiring] Applied AI Engineer @Emberline

Role Description

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.

Key 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.
  • Workflow Integration: Connect AI tools to existing systems like CRMs, helpdesks, marketing platforms, and codebases.
  • Rapid Prototyping: Test new AI applications quickly. Prove value in days or weeks, not months.
• Vendor & Tool Evaluation
  • Landscape Monitoring: Stay current on AI tooling: what's shipping, what's vaporware, what's actually production-ready.
  • Vendor Screening: Evaluate vendors, run trials, negotiate pricing.
  • 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 company teams to use and maintain the tools you deploy.
  • Documentation: Build simple, usable guides for each implementation.
  • Cross-Portfolio Learning: What works at one portfolio company should benefit the others.
• 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.

Qualifications

• Experience in Product Management, Solutions Engineering, Technical Operations, or similar roles.
• Hands-on experience with AI/ML tools in a professional context.
• Strong understanding of APIs, integrations, and how systems connect.
• Excellent communication skills.
• Comfort with ambiguity.
• This is a remote role but on-site engagements, rapport building and investigations are a key requirement, which will require travel.

First 90 Days

• Audit the portfolio.
• Get something live.
• Build handoff documentation.
• Establish a vendor shortlist.
• Establish the working rhythm.