Internal AI Operations Engineer
Swoogo · United States
- Hybrid
- Full-time
- $120,000 / year
- United States
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Job highlights
- Build internal AI tools and workflows.
- Integrate AI APIs like Claude and OpenAI.
- Manage production tools and deployment.
- Collaborate with cross-functional teams.
- Drive AI impact across the organization.
About the role
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
About Swoogo & How We Work
Learn more about Swoogo, how we work, and our Perks & Benefits.
Key skills/competency
- AI Operations Engineer
- AI APIs and LLMs
- Integration
- Production Tools
- SaaS
- Startup Environment
- Vercel
- GitHub
- Stakeholder Management
- Problem Solving
Skills & topics
- AI Operations Engineer
- AI
- LLM
- API Integration
- SaaS
- Startup
- Vercel
- GitHub
- Automation
- Workflow Development
How to get hired
- Tailor your resume: Highlight experience with AI APIs, LLMs, and deploying applications on platforms like Vercel and GitHub. Showcase projects solving business problems with AI.
- Showcase your portfolio: Provide examples of built AI tools, automations, or workflows, demonstrating tangible outcomes and stakeholder collaboration.
- Understand Swoogo's mission: Research Swoogo's focus on building events and their internal culture of intention, creativity, and action.
- Prepare for technical questions: Be ready to discuss your experience with API integrations, token budgeting, security, and version control in AI development.
- Demonstrate communication skills: Practice explaining technical solutions to non-technical audiences and how you translate business pain points into AI solutions.
Technical preparation
Deepen knowledge of AI APIs (Claude, OpenAI).,Practice deploying apps on Vercel/similar platforms.,Build personal projects with AI integrations.,Familiarize with GitHub for version control.
Behavioral questions
Describe a manual process you automated.,How do you translate business needs to tech?,Tell me about a proactive solution you built.,How do you manage competing stakeholder requests?
Frequently asked questions
- What is the primary focus of the Internal AI Operations Engineer role at Swoogo?
- The primary focus of the Internal AI Operations Engineer at Swoogo is to build and manage reusable internal AI tools and infrastructure that the entire organization can leverage to enhance efficiency and scale success. This involves taking requests from various departments, prioritizing them, and developing production-ready AI solutions.
- What distinguishes this role from a traditional DevOps or SRE position?
- This role is a hybrid between a solutions engineer and a hands-on AI builder. Unlike traditional DevOps/SRE, the focus is on proactively identifying business problems, determining how AI can solve them, and shipping the AI-powered solution, rather than solely managing infrastructure or site reliability.
- What kind of experience is essential for the Internal AI Operations Engineer at Swoogo?
- Essential experience includes 3-5 years in a SaaS, tech, or startup environment, building and shipping AI-powered tools or workflows. Proficiency with AI APIs (Claude, OpenAI), deployment platforms (Vercel), and code management (GitHub) is crucial. Experience translating business needs into technical AI solutions is also key.
- What are the key responsibilities of an Internal AI Operations Engineer at Swoogo on a day-to-day basis?
- Day-to-day responsibilities involve taking AI tool requests from stakeholders, prioritizing them, building AI-powered tools using APIs and platforms like Vercel, auditing existing integrations, establishing best practices for AI tool usage, managing the full lifecycle of internal tools, and proactively identifying opportunities for AI impact.
- How does Swoogo approach internal AI development and collaboration?
- Swoogo fosters an environment of intention, creativity, and action. The Internal AI Operations Engineer acts as a bridge between Engineering and other departments, making AI tooling accessible and reliable infrastructure for non-technical teammates, emphasizing ownership and proactive problem-solving.
- What are 'MCP integrations' and why are they relevant to this role?
- MCP integrations likely refer to specific internal workflows or systems at Swoogo that the AI Operations Engineer will work with. Experience with MCP integrations and agentic AI workflows is considered a plus, indicating a need to understand and build upon Swoogo's existing or preferred technical stack for AI solutions.
- How important is it to have a traditional engineering background for this role?
- A traditional engineering background is beneficial, but Swoogo also values non-traditional paths. If you have a background in sales, marketing, or operations and have taught yourself to build AI solutions, or if you're an engineer who has specialized in AI tooling early on, that experience is highly relevant and valued.