Internal AI Operations Engineer

Who You Are

You're the person who sees a clunky manual process and immediately starts mentally wiring up the solution. You don't wait for a product backlog or a sprint ticket—you spot the problem, figure out how AI can solve it, and ship something that works. Equal parts builder, translator, and strategist, you live at the intersection of technical capability and real-world business impact.

You've gone deep on AI APIs and LLMs—not just prompting, but integrating them into production tools that people actually depend on. You know how to manage credentials, think through token budgets, and make sure what you ship is secure, version-controlled, and maintainable. You're comfortable in GitHub, fluent in deployment platforms like Vercel, and you treat documentation as part of the job, not an afterthought.

What sets you apart is your ability to move between worlds. You can sit down with a Sales rep or an HR manager, absorb their pain, and walk away with a clear technical plan. You've probably done this across multiple business functions—and you've learned that the best solutions don't come from the most complex architecture, they come from truly understanding what someone is trying to accomplish.

At Swoogo, we're passionate about building events that bring people together, and that same spirit drives how we work internally: with intention, creativity, and a bias toward action. You share that energy. You're not waiting to be handed a problem—you're already three steps ahead, identifying where AI can drive the most leverage and building the thing that proves it.

You'll be the go-to for internal teams across the org, the bridge between Engineering and everyone else, and the person who makes AI tooling feel less like magic and more like infrastructure. If that kind of ownership excites you, you'll thrive here.

About the Role

We are seeking a leader to centralize reusable internal AI tools and infrastructure that the entire organization can leverage and depend on to scale our success.

As our Internal AI Operations Engineer, you will be the go-to builder for AI-powered internal tools and workflows at Swoogo. You will take requests from across the organization (Sales, RevOps, CX, Marketing, HR, and more), prioritize them strategically, and turn them into production-ready tools that are secure, version-controlled, and usable by non-technical teammates.

This is not a traditional DevOps or SRE role. Think of it as a hybrid between a solutions engineer and a hands-on AI builder. You will be the person who spots a problem, figures out how AI can solve it, and ships the solution, whether that means wiring up MCP integrations, utilizing new and existing toolsets, building a prioritization engine, or creating an intelligence tool to help existing teams work smarter and more efficiently.

Day to day, you will:

Intake, prioritize, and execute internal AI tool requests from stakeholders across the org

Build and ship internal tools using AI APIs (Claude, OpenAI, etc.), MCP workflows, and modern deployment platforms (Vercel, GitHub)

Audit and document existing MCP integrations to identify which are reliable, which have data gaps, and which should be deprecated or improved

Establish best practices for how internal teams use AI tools, including security, credential management, token usage, and version control

Manage the full lifecycle of internal tools: scoping, building, deploying, credentialing, monitoring usage, and iterating based on feedback

Identify opportunities proactively rather than waiting to be assigned tasks, bringing a creative and strategic lens to where AI can drive the most impact

Collaborate with Engineering and Product to bridge gaps between internal tooling needs and platform capabilities

What You've Done Before

3-5 years of experience

Built and shipped internal / external tools, automations, or AI-powered workflows in a SaaS, tech, or startup environment

Worked with AI APIs and LLMs (Claude, OpenAI, etc.) beyond just prompting, meaning you have integrated them into applications, managed API keys and token budgets, and handled authentication

Deployed applications using platforms like Vercel, Netlify, or similar, and managed code in GitHub with proper version control

Worked across multiple business functions (Sales, Ops, Marketing, CS) and translated their pain points into technical solutions

Demonstrated a portfolio of projects (personal or professional) where you solved complex problems using AI, showing tangible outcomes that would have traditionally required weeks of engineering effort

Managed competing priorities and stakeholder requests without a formal product org handing you a backlog

Worked with CRM and GTM tools like Salesforce and understanding how data flows (and breaks) between them

Acted as an excellent communicator, absorbing and understanding complex requirements, extrapolating the end goal and definition of success, and creatively exploring and building solutions

Possess strong interpersonal and training skills required to work hands-on with non-technical teams, ensuring they can easily adopt complex solutions, understand the underlying logic, and become self-sufficient in their use.

It'd Be Great if You've Done This

Experience with MCP (Model Context Protocol) integrations and agentic AI workflows

Built tools that connect multiple data sources 

Background in a non-traditional engineering path: maybe you started in sales, marketing, or ops and taught yourself to build, or you are an engineer who leaned hard into the AI tooling wave early

Created internal documentation, runbooks, or training materials to help non-technical teammates adopt AI tools

Experience with event technology, SaaS platforms, or B2B GTM environments

Familiarity with data architecture concepts: relational fields, API schemas, data integrity, and how systems like Salesforce model relationships

Built a product feature prioritization framework or internal request intake system

Swoogo & How We Work

Learn more about Swoogo, how we work, and our Perks & Benefits.