GTM Engineer

ProviderTrust•Nashville, TN

3d•Hybrid

About The Position

ProviderTrust is building an internal AI/GTM intelligence layer as the strategic backbone of our Revenue Operations function — the connective tissue between Commercial, Ops, and Marketing that turns fragmented systems and manual workflows into a signal-driven revenue engine. The GTM Engineer owns the build: designing, shipping, and maintaining the automations, integrations, and applied-AI tooling that let RevOps operate at scale, not by hand. This is a builder's role, not an analyst's. You'll sit inside the AI & GTM Innovation pillar of RevOps and work in close partnership with Client Intelligence, Commercial Operations, Systems & Tooling, and Data & Forecasting to identify where AI and automation create leverage, then build it. Building the initial AI infrastructure will require working closely with Product and Engineering; this is not a role that builds in isolation from the core platform team. Role Phasing & Success Expectations Our current data foundation is not yet scaled to support the automation and AI-driven outcomes this role is ultimately aimed at. We're being explicit about that going in: Phase 1 (first ~90 days): The primary mandate is establishing the data infrastructure, including a data lake, that the AI/GTM layer will run on. This is built in close partnership with Product and Engineering, not independently. Success here depends as much on cross-functional alignment as on technical execution. Early wins look like reliable data flows and integration architecture, not automation ROI or GTM outcomes yet. Phase 2 (post-foundation): Once the data layer is live, the mandate shifts to the automations, applied-AI tooling, and workflow agents described below. This is where "signal-driven revenue engine" outcomes become fair to expect and measure. Candidates should come in expecting to build the foundation before the flashier layer on top of it, and should be energized by that sequencing, not frustrated by it.

Requirements

Proof-of-Work Portfolio: a practical track record of shipping automation and insight
Experience designing or building AI automation coming from desperate sources (data warehouse, CRM Salesforce, BI tools, ETL data sources…). This role starts at the foundation layer, not just the automation layer on top of it
Experience building automations/integrations across SaaS tools (Slack, Gmail/Google Workspace, Zoom, CRM systems) using platforms like n8n, Zapier, or custom scripting
Hands-on experience building with LLMs/AI agents in a production or internal-tooling context, not just prompting, but architecting
Strong scripting/programming ability (Python and/or JavaScript) and comfort working directly with APIs
A GTM or RevOps background, or enough exposure to sales/CS/marketing motions to know what "useful" looks like to a rep or CSM
Bias toward shipping: comfortable owning a build end-to-end with limited scaffolding, in a function still being stood up
Team player mentality and a ‘Can Do’ attitude

Nice To Haves

Prior experience in a healthcare, compliance, or data-integrity-adjacent SaaS business
Project management experience with scoping, documenting, and implementation steps.

Responsibilities

Work as an embedded partner with Product and Engineering to build that infrastructure, aligning RevOps' data needs with the core platform's architecture and roadmap
API & Data Architecture: design and build automations across our GTM stack (e.g., n8n, Slack, Gmail, Zoom, CRM) that eliminate manual handoffs in the revenue lifecycle
Build and maintain applied-AI tooling that supports internal GTM use cases — lead/account intelligence, forecasting inputs, rep-facing copilots, and workflow agents
Partner with Commercial and Ops leadership to translate operational pain points into engineered solutions, not just dashboards
Prototype quickly, ship iteratively, and instrument what you build so impact is measurable
Work alongside Data & Forecasting to ensure automations and AI tooling are grounded in clean, trustworthy data
Stay current on applied-AI and GTM-engineering practices and bring outside frameworks in where they sharpen our approach
Build and manage multi-channel sequences often representing more than 1 system at the time. (Example: such as LinkedIn → email → cold call → SMS)
Where possible, integrate into one workflow multiple existing digital processes
Report on automation ROI: such as time saved, revenue impact, headcount savings, accelerated sales cycle, bypass manual process, etc. (this list can be defined periodically with your leader)

Benefits

Hybrid schedule: 2 days in office
16-week paid primary caregiver with a 2-week phase-back leave policy
4-week paid secondary caregiver leave policy
Team members are encouraged to experiment and share what they learn
Competitive base salary and incentive package
401k matching
HSA employer contribution
company-paid life and disability insurance
Medical, dental, and vision benefits: PT pays 80% of your premiums
Access to a range of free mental health and well-being resources
Unlimited PTO
11 paid holidays
Flexible work schedule
Internal professional growth, development, and mobility
Daily all-company morning huddles to sync up across the business
In-office experience: fully stocked kitchen, ergonomic desk setup, and many celebrations!
Remote experience: home office set-up with technology provided, remote-friendly meetings and celebrations, and interest-specific Slack channels for connecting across teams
Fitness stipend
Cell phone reimbursement