Additional Information
At NiCE, we don't limit our challenges. We challenge our limits. Always. We're ambitious. We're game changers. And we play to win. We set the highest standards and execute beyond them. And if you're like us, we can offer you the ultimate career opportunity that will light a fire within you.
AI Software Engineer - Cloud AI Platforms
At NICE, we are not just building software-we are transforming how cloud operations are run using AI. We are building intelligent platforms that can understand system behavior, make decisions, and automate real-world operational workflows at scale. If you're excited about applying AI beyond chatbots into real production systems, this is an opportunity to work on meaningful, high-impact problems.
What's the role all about?
As an AI Software Engineer, you will be part of a team building AI-powered operational platforms that integrate across monitoring systems, CI/CD pipelines, ticketing tools, and cloud infrastructure. You will work on designing and implementing intelligent workflows, integrating AI models, and building scalable systems that automate complex operational tasks.
This is a highly hands-on role focused on building, integrating, and scaling AI-driven solutions in production environments .
How will you make an impact?
Build and scale AI-driven workflows and automation systems
Develop integrations with systems like monitoring platforms, ticketing tools (ServiceNow, Jira, OpsGenie), CI/CD pipelines, and cloud services
Design and implement APIs, tools, and data pipelines that power AI-driven decision-making
Work on LLM integrations, prompt engineering, and orchestration layers - streaming responses, function calling, tool use, RAG pipelines, agentic orchestration
Build and maintain full-stack AI applications using TypeScript, React, and Next.js - from user dashboards and personalized experiences to real-time analytics and interactive tools
Translate real-world operational problems into automated, intelligent solutions
Collaborate with Product, SRE, and Infrastructure teams to deliver end-to-end capabilities
Improve system performance, reliability, and observability
Build evaluation and observability systems - measure model capabilities, monitor output quality, and create dashboards that keep the product improvable
Create reusable platforms and tools that accelerate development - component libraries, shared abstractions, internal tooling that multiplies team productivity