AI Enablement Engineer

Applause

22h•Remote

About The Position

We're looking for an AI Enablement Engineer to drive AI adoption across every team at Applause. You 'll build and maintain a monthly roadmap of AI-powered workflows for departments like Sales, Customer Success, Marketing, Finance, and HR/TA, then actually implement them: standing up tools, wiring integrations into our core systems, training the team on how to use them, and tracking whether they're moving the needle. This is a builder role, and you'll work closely with our CTO and Chief Architect, who own the broader AI vision and governance, while you own execution.

Requirements

Bachelor's degree in Computer Science, Data Science, Engineering, or a related technical field (or equivalent hands-on experience)
2–4 years of experience in AI/LLM implementation, workflow automation, technical business operations, or a related hands-on technical role
Able to write and modify code for simple, internal business applications (even if AI writes most of it)—production-grade or engineering-quality code is not required
Demonstrated experience building integrations or automations (e.g., Zapier, Make, APIs, low-code/no-code platforms)
Working knowledge of modern AI tools Claude, Copilot, and similar) and how to apply them to business workflows
Comfortable working cross-functionally with non-technical teams (Sales, CS, Marketing, Finance, HR) to scope and deliver workflows
Strong communicator who can train and troubleshoot with non-technical users
Detail-oriented with strong ownership over initiatives, start to finish
Very effective in a remote work environment

Responsibilities

Build a monthly roadmap of AI workflows to design and ship, prioritized by productivity or cost impact, for every department (except Product and Engineering)
Identify manual, repetitive work across departments and design AI-driven workflows to replace or accelerate it
Ship the workflows you scope: configure tools, build automations, and get them into daily use, not just document recommendations
Iterate and fine-tune workflows post-launch based on usage and feedback
Support system implementations for AI and adjacent tools, partnering with the CTO and Engineering on technical requirements and data access
Connect AI tools into core business systems (CRM, HRIS, finance tools, Slack, etc.), so workflows run inside the systems teams already use
Evaluate and pilot new AI tools for specific departments and use cases, and recommend what to adopt, pause, or retire
Train department teams on the workflows and tools you build, and follow up to make sure they're actually being used
Troubleshoot adoption issues directly with end users rather than escalating them
Track usage and cost of AI tools by team and use case, and run monthly ROI reporting
Report progress monthly to the CTO on workflow delivery, adoption, and productivity/cost impact
Level up teams to build and own their own AI workflows over time, so departments grow more self-sufficient rather than depending on you for every change