AI Transformation

Ent•San Francisco, CA

23h•Hybrid

About The Position

We are hiring a builder who will drive AI transformation for the operation of Ent's rapidly-growing business. This person's job is to deeply understand how Ent's operations actually runs, then hands-on build the agents, automations, integrations, and data tooling that make every function faster and sharper. This is a rare mix of consultant and engineer. You will embed with teams to learn their work, find the highest-leverage problems, and then go build the solution yourself — from prototype to production to adoption. You'll start by prioritizing business systems (the connective tissue between CRM, support, finance, and ops) because that's where reliable automation compounds fastest, then expand outward to whichever function has the biggest opportunity. You'll report to the Chief of Staff with direct CEO sponsorship, giving you cross-functional access and air cover to change how work gets done.

Requirements

Demonstrated hands-on building with LLMs: prompt engineering, working with model APIs (Anthropic, OpenAI, etc.), retrieval/RAG, structured outputs, and at least one agent framework (e.g., LangGraph, CrewAI).
Working software engineering ability: Python and/or TypeScript, comfort with REST APIs and one cloud, and enough SQL/data handling to be dangerous.
Business-systems fluency: experience integrating or automating CRM/support/ops tools (e.g., Salesforce/HubSpot, Zendesk) and workflow platforms (Zapier/Make/n8n or code).
A process mind: can decompose a messy business process, quantify the cost, and design a measurably better one.
Consultative communication: can run a working session with a sales leader and a check-in with an exec in the same day, and translate between them.
Bias to ship: gets a working prototype in front of users fast and iterates.
High-degree of discretion and integrity: in building these internal systems, you will have access to sensitive company information.
Equivalent demonstrated building ability can substitute for a degree, especially at entry/IC2. A strong portfolio of shipped AI/automation work outweighs credentials.

Responsibilities

Embed with each business function — sales, exec staff, operations, customer success , and business systems — to map how work actually gets done and where AI creates leverage.
Prioritize business systems first: instrument, connect, and automate the core stack (CRM, support, finance/ops tooling) so downstream automations are reliable.
Design and personally build scalable, cost-effective AI solutions end-to-end: agents and copilots, workflow/process automation, and data & analytics that remove manual work and speed decisions.
Own solutions from discovery → prototype → production → adoption → measurement; you ship, you don't just advise.
Integrate AI into Ent's systems responsibly, respecting data governance and security — we hold ourselves to the standard we sell.
Establish lightweight standards, evaluations, and guardrails so automations are trustworthy, observable, and maintainable.
Enable teams through documentation, onboarding, and training so adoption sticks after you move to the next problem.
Partner with R&D to reuse Ent's own AI capabilities internally where it makes sense.
Maintain a prioritized, ROI-ranked internal AI backlog and report impact to the CEO/CoS.