AI Enablement Engineer, IT
McLean, VAAll locationsMcLean, VAMountain View, California, United StatesNew York City, NYTampa, FL On-site
$128,459–$143,681 a yearJobFig found this opening at its original source and checks that it remains available.
About the role
We are seeking an AI Enablement Engineer to join our new Corporate AI Enablement & Efficiency team — the group responsible for turning AI from a buzzword into everyday leverage for the entire company. You will design and build the automations, integrations, and AI agents that connect our applications, eliminate manual work, and help every team do more with the tools they already have. Your work will directly shape how a 1,000-person organization adopts AI: safely, measurably, and at scale. You will wire up production workflows, connect systems through APIs, and stand up MCP servers, AI skills, and agents that give teams reliable, governed access to large language models. Other days you will be out in the business, spotting the manual, repetitive work worth automating and shipping solutions that stick. Throughout, you will build like an engineer: real error handling, observability, evaluations, and guardrails — and you will keep Security and Data close so everything you ship stays compliant. You will work at the frontier of applied AI: agents, MCP, retrieval, and orchestration with the autonomy to build real things that of colleagues. If you love turning messy manual processes into elegant solutions and want to help define how a company puts AI to work, this is an exciting opportunity to make a meaningful impact.
What you'll bring
- 4+ years building integrations, automations, or software in a professional environment including production work with LLMs or AI agents.
- Hands-on experience with workflow-automation.
- Strong API fluency (REST / JSON, OAuth, webhooks) and the ability to read and write code in Python, Go, JavaScript / TypeScript or similar.
- Practical experience building with large language models: prompting, structured outputs, and at least one of RAG, tool / function-calling, or agents.
- A production mindset - error handling, logging and observability, testing or evaluations, and secure handling of secrets and sensitive data.
- Ability to work directly with non-technical colleagues: understanding a business process and translating it into a reliable, well-documented automation.
- Understanding of data privacy, security, and responsible-AI considerations, and a habit of partnering with Security and Data teams.
- Experience building or deploying MCP servers, AI agents, or custom AI skills.
- Familiarity with the modern AI stack: orchestration frameworks, vector databases, and evaluation tooling.
- A portfolio of shipped automations or agents that shows production quality, not just prototypes.
- Experience integrating common business systems and their APIs (HRIS, ITSM, CRM, finance, and collaboration suites).
- Exposure to enterprise AI tools (AI copilots, chat assistants) and helping teams adopt them effectively.