AI GTM Engineer, Revenue Operations

ProviderTrust•Nashville, TN

8h•Hybrid

About The Position

ProviderTrust is hiring an AI GTM Engineer to embed AI-powered tools and workflows across Revenue, Marketing, and Customer Success. The role focuses on improving productivity, enabling self-service access to data, automating reporting, and producing high-quality customer-facing assets. The engineer will own AI systems, drive adoption, and ensure solutions are scalable, secure, and aligned with business goals. The role involves identifying and deploying high-impact AI use cases, building production or internal AI agents and workflow automations, integrating the go-to-market technology stack, and connecting trusted CRM and BI data. The engineer is expected to prototype quickly, add appropriate guardrails and human review for higher-risk decisions, and own shipped solutions through monitoring, error handling, and documentation. They will establish feedback loops and measure adoption, productivity gains, and business impact, including ROI, time saved, revenue impact, cycle-time reduction, and headcount leverage. ProviderTrust is a Nashville-based company with more than 100 employees. It provides exclusion monitoring and primary source verification solutions to healthcare organizations. The company describes its culture as empathetic, inclusive, creative, fast-paced, resourceful, and supportive of experimentation, including with AI.

Requirements

At least 2 years of experience with Claude Code.
At least 5 years of experience in Revenue Operations, Sales Operations, Business Systems, or a related role.
Hands-on experience with CRM platforms such as Salesforce and BI tools such as Domo or Tableau.
Familiarity with AI/LLM tools, prompt engineering, or workflow automation.
A portfolio of automations or AI solutions personally built and shipped, with an ability to explain the problem solved and how it was addressed; the posting states this is non-negotiable and that resume specifications are secondary to demonstrated work.
Hands-on experience building with LLMs and agents in production or internal tooling, including tool calling, MCP, and evaluating output quality; the role requires architecture, not just prompting.
Experience managing cross-functional projects and driving adoption of new tools or processes.
Ability to prioritize multiple initiatives.
Strong communication skills and ability to work effectively across teams.
Strong background in programming languages such as Python, SQL, R, or related languages.
Hands-on experience with API integrations.
A bias toward shipping and ownership of end-to-end builds in a function that is still being established.
Bachelor's or master's degree in information systems, computer science, data science, AI, engineering, or equivalent practical experience.

Nice To Haves

Experience deploying AI or automation solutions within go-to-market teams.
Knowledge of APIs, integrations, and no-code or low-code platforms.
Experience building self-service analytics or automated reporting solutions.
Familiarity with data governance, security, and compliance best practices.

Responsibilities

Identify, prioritize, and deploy high-impact AI use cases across go-to-market teams.
Design and implement AI-powered workflows that improve productivity and reduce manual effort.
Enable natural-language access to CRM and BI data to improve self-service analytics.
Own and manage the AI technology stack, including LLM platforms, copilots, and integrations.
Prototype quickly and put working versions in front of users; add guardrails and human-in-the-loop checkpoints where decisions carry risk.
Own shipped solutions, including monitoring, error handling, and documentation.
Establish feedback loops and continuously improve AI tools, prompts, and workflows.
Track and report adoption, productivity gains, and revenue impact of AI initiatives.
Report on ROI, including time saved, revenue impact, cycle-time reduction, and headcount leverage.
Build AI agents and workflow automations using Claude, MCP connectors, APIs, Zapier, Claude Code, DOMO MCP, and custom Python or JavaScript.
Connect CRM, BI, and funnel data so agents can work from clean, trusted data.
Integrate go-to-market systems such as Salesforce, Slack, Gmail, Zoom, and call-recording solutions, writing back to systems of record rather than creating shadow processes.
Build lead and account intelligence, forecasting inputs, rep-facing copilots, and multichannel sequences such as LinkedIn, email, calls, and SMS.
Manage cross-functional initiatives and drive adoption of new tools and processes.