AI Software Engineer - Cloud AI PlatformsAt 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
Key Responsibilities- Design and develop scalable backend systems for AI-powered platforms
- Build and maintain AI integrations, workflows, and automation pipelines
- Implement REST APIs, microservices, and event-driven architectures
- Design and implement database schemas and queries for complex domains - tracking, engagement, reporting
- Work with both structured and unstructured data for AI use cases
- Contribute to CI/CD pipelines, testing, and deployment automation
- Troubleshoot and optimize production systems
- Collaborate with cross-functional teams to deliver high-quality solutions
- Contribute to reusable frameworks and engineering best practices
- Prototype fast - move from concept to working demo in days, ship incrementally
What we're looking for- 10+ years of software engineering experience, strong focus on full-stack web development
- Expert in TypeScript and React - performance optimization, modern patterns (hooks, context, suspense), component architecture
- Production experience with Next.js - App Router, Server Components, API routes, SSR/SSG, edge deployment
- Hands-on experience with LLMs - prompt engineering, streaming APIs, function calling, tool-use, chaining and orchestration patterns
- Experience with Vercel AI SDK - unified LLM provider interface, streaming, structured output, tool calling across OpenAI/Anthropic/Google/xAI
- Model Context Protocol (MCP) - building or consuming MCP servers for extensible AI tool use
- Strong backend fundamentals - Node.js or Python, REST/GraphQL APIs, relational databases, Redis, auth
- Solid database design - PostgreSQL, Drizzle ORM, schema modeling for complex domains, query optimization, migrations
- Experience building scalable, distributed systems in cloud environments (AWS / Azure)
- Working knowledge of CI/CD, Docker, Kubernetes
- Familiarity with Tailwind CSS, Radix UI and modern component-driven UI development
- High agency - you operate independently in ambiguous environments, take ownership of problems, and drive them to completion
- Strong problem-solving and analytical skills
- Ability to work in a fast-paced, evolving environment
- Communicate effectively with both technical and non-technical stakeholders
Nice to have- Experience building agentic coding tools, AI agent frameworks, or developer-facing SDKs/APIs (Claude Agent SDK, OpenAI Agents SDK)
- Experience with Vercel ecosystem - Next.js, AI SDK providers, Turbopack
- Background in evaluation frameworks - measuring model capabilities, collecting human feedback at scale, A/B testing outputs
- Experience with sandboxed execution environments for safely running AI-generated code
- Built research tools, experimentation platforms, or scientific software
- Proficiency with Python - FastAPI/Django, data pipelines, ML tooling
- Knowledge of observability tools (Grafana, Prometheus, Sentry, etc.)
- Experience building automation or internal platforms
- Familiarity with real-time features - WebSockets, streaming UX, collaborative interfaces
- Knowledge of advanced web technologies - WebGL, WebAssembly, web workers, PWAs
- Experience with alternate JS runtimes - Bun, Deno
- Built open-source tools or platforms with active user communities
- Strong quantitative foundation (math, physics, or related fields)
Representative ProjectsThings you might build in this role:
- Interfaces for collecting and managing human feedback on model outputs at scale
- Experiment orchestration platforms - launch, monitor, and analyze complex AI research runs
- Visualization tools that help understand model behavior and identify failure modes
- Reusable components and frameworks that enable rapid development of new AI applications
- Sandboxed execution environments for safely running AI-generated code
- AI-powered personalization engines - tutoring, content generation, adaptive features
- Workflow builders that let non-engineers orchestrate AI capabilities visually
- Enterprise integrations - ServiceNow, Salesforce, Confluence, Jira
