Senior Full-Stack Software Engineer, AI & Data

Everbridge; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Everbridge Bengaluru is seeking a versatile full-stack engineer who can design, build, and ship internal tools and services end-to-end. You will work across the stack—backend services and APIs, front-end interfaces, data integrations, and the automation glue that ties them together.

AI is a tool in your kit, not the sole focus, with emphasis on reliability and breadth across projects. You’ll collaborate with the Applied AI Engineer to integrate LLMs, RAG, and agent capabilities into usable

Qualifications

• Proficient in building production-grade software across backend, APIs, and frontend.
• Experience shipping end-to-end internal tools and services.
• Ability to wire AI tools (LLMs, RAG, agents) into products.

Responsibilities

• Build across the stack: backend services, APIs, front-end interfaces, and deployment glue.
• Move between projects as priorities shift to deliver value quickly.
• Integrate AI capabilities into usable software with the Applied AI Engineer.
• Engage with cross-functional teams to understand problems and deliver effective solutions.
• Ship reliably from idea to production and beyond.

Skills

Full-stack

API design

Python/TypeScript

AI integration

Data pipelines

Autonomy

Tools

AWS

Docker

Kubernetes

CI/CD

Job description

About The Team

We’re the company’s internal AI & Data team — a small, fast-moving pod. Our mission is to make the rest of the company dramatically more capable, using AI and Data to automate work, unlock insight, and build the tools and systems teams rely on.

About The Team

We’re the company’s internal AI & Data team — a small, fast-moving pod. Our mission is to make the rest of the company dramatically more capable, using AI and Data to automate work, unlock insight, and build the tools and systems teams rely on.

This role is the versatile builder who turns all of that into working software — and who can pick up whatever the moment demands.

The role

You’re a builder, full stop. You’ll work on many things — internal tools, services, interfaces, integrations, automation. You’ll move fluidly between them as priorities shift. This is deliberately a broad, flexible seat: we’re not hiring for one stack or one problem, we’re hiring someone who can build whatever the company needs next and do it well.

AI is a tool in your kit, not the thing you specialize in. You don’t need to design retrieval systems or agents from scratch — but you’re comfortable working with them, wiring them into products, and shipping the software around them. Your superpower is range and reliability: you take things from idea to shipped, across the stack, without needing a narrow lane.

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

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.