About the Role

Hello Heart is building AI as a company capability, not just in our product, but in how every function operates. We're standing up a small, high-impact AI Enablement team to make that real. Reporting into our VP, Data and AI, you will work directly with leaders across the company to identify manual, time-intensive workflows and rapidly prototype solutions that meaningfully reduce effort and improve outcomes. This role is the builder on that team: the person who turns business problems into working AI solutions, fast. The success in this role will be measured by the impact on efficiency, as measured by the adoption of valuable AI products

You won't be writing strategy decks or facilitating workshops. You'll be sitting with a VP who says "this process takes my team 6 hours a week" and coming back 5 days later with a working prototype that cuts it to 30 minutes. If that sounds like your kind of work, keep reading.

Responsibilities

In your first 6 months, you'll have:

• Shipped 5–10 internal AI workflows that are in daily use across Hello Heart, not prototypes, not demos, real tools people rely on
• Built agents, automations, and LLM-powered applications that measurably reduce cycle time, error rates, or manual effort in targeted workflows
• Created reusable patterns and components that accelerate every subsequent build
• Published an internal library of playbooks, templates, and working examples that other teams can learn from and extend

What the Work Looks Like

• Discover: Partner with functional leaders to understand their highest-friction workflows. Identify where AI can make a material difference, not where it's theoretically possible, but where the ROI is obvious.
• Build: Design and ship secure AI-powered workflows end-to-end. This means prompting, agent design, API integrations, workflow orchestration, and whatever else it takes to get a working solution into people's hands.
• Iterate: Measure usage and impact. Kill what's not working. Double down on what is. Move from prototype to production-grade within weeks, not quarters.
• Scale: Document what works so it can be replicated. Build patterns, not one-offs. Train teams to use and extend what you've built.

Qualifications

• 5+ years of experience in applied AI, product engineering, workflow automation, or a technical ops/product ops role where you actually built things
• Experience working with GTM teams across sales, marketing, CS 
• Experience working in highly regulated environments 
• Experience with change management or driving adoption of new internal tools
• Hands-on proficiency with LLMs, agent frameworks, prompt engineering, and workflow automation platforms, you can build a working AI application end-to-end without waiting for an engineering team
• Strong intuition for translating messy business problems into scoped, buildable solutions
• Comfort working directly with senior leaders, you can run a discovery conversation with a VP and walk away with a clear use case
• Python scripting, API integration, or light engineering skills beyond no-code platforms
• Bias toward shipping over planning. You'd rather show a working prototype than a requirements doc
• A portfolio of AI workflows, agents, or internal tools you've built and can walk us through (we'll ask for this)

Nice to Have

• Healthcare, health-tech, or regulated industry experience
• Familiarity with data platforms, BI tools, or analytics workflows

The US base salary range for this full-time position is $200,000.00 to $225,000.00. Salary ranges are determined by role and level. Compensation is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the annual salary and bonus only, and do not include equity or benefits.