Full-Stack AI & Data Engineer
Job Description
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What you’ll do
- Build across the stack. Design and ship internal tools and systems end to end — back-end services and APIs, front-end interfaces, data integrations, and the deployment and infrastructure glue that makes them real.
- Work on many things. Move between projects and problem types as priorities shift — one week a workflow-automation tool, the next an internal dashboard, the next helping ship an AI-powered feature. Breadth is the point.
- Put AI to work. Integrate the LLM, RAG, and agent capabilities the team builds into usable software, partnering closely with the Applied AI Engineer to turn intelligence into product.
- Enable the company. Sit with teams across the business, understand their problems, and build the right solution — measured by how much more effective you make everyone else.
- Ship reliably. Own what you build through to production and beyond, with the quality and judgment to know when good-enough-shipped beats perfect-delayed.
What you'll bring:
- Strong full-stack engineering. You write production-grade code and build comfortably across the stack — back end, APIs, and front end (e.g. Python and/or TypeScript with a modern web framework). You’re not boxed into one layer.
- Range and adaptability. A track record of picking up unfamiliar problems and shipping — you’re energized by variety, not thrown by it.
- Comfort with AI as a tool. You’ve worked extensively with AI — integrating APIs, building features on top of models — even if AI isn’t your specialty.
- A builder who talks to people. You can understand a non-technical team’s problem and turn it into a working solution. Internal enablement rewards engineers who listen as well as they build.
- Data fluency. Enough comfort with pipelines, databases, and structured/unstructured data to work directly with what your software touches.
- Autonomy in a small team. You thrive without heavy process, set your own direction, and are happy wearing whatever hat the moment calls for.
Bonus points
- Experience building internal tools or platforms that other teams depend on.
- Cloud, DevOps, or deployment experience — CI/CD, containers, infrastructure-as-code.
- Hands-on experience shipping LLM-powered features in production.
- A portfolio of varied systems you’ve built end to end.
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Everbridge
View Company ProfileEverbridge is a global leader in Critical Event Management (CEM) and enterprise safety software, dedicated to keeping people safe and organizations running during high-impact situations. Founded in 2002 in the aftermath of 9/11, and headquartered in Burlington, Massachusetts, the company provides a highly scalable SaaS platform that automates and accelerates operational responses to massive disruptions. Under the hood, the Everbridge CEM platform continuously aggregates and analyzes global threat data, cross-references it with the real-time locations of employees and physical assets, and automatically executes predefined, multi-channel communication workflows. Their primary target audience includes global Fortune 500 enterprises, major healthcare networks, and entire national or local governments that require mission-critical mass notification systems for events ranging from severe weather and active shooter scenarios to massive IT outages and supply chain disruptions. What sets Everbridge apart in the risk management ecosystem is its unparalleled scale and reliability; their infrastructure successfully delivers billions of life-saving messages annually across thousands of municipalities, fundamentally bridging the gap between digital threat intelligence and real-world crisis mitigation.
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- Never pay for a job application.
- Do not share sensitive bank info.
- Verify the client before starting work.