Principal AI Software Engineer

NICE· Seattle, Washington, United States; USA - Atlanta, GA; USA - Hoboken, NJ; USA - Richardson, TX; USA - Sandy, UT· greenhouse· publié le 26/06/2026
Indispensable :TypeScriptPythonCSSReactNext.jsNode.jsGraphQLTailwindAWSAzureDockerKubernetesCloudBackendFullstackDevOpsCI/CDMicroservicesAIGamingPrincipal

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.

Principal 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

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 Projects

Things 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

About NiCE

NICE Ltd. (NASDAQ: NICE) software products are used by 25,000+ global businesses, including 85 of the Fortune 100 corporations, to deliver extraordinary customer experiences, fight financial crime and ensure public safety. Every day, NiCE software manages more than 120 million customer interactions and monitors 3+ billion financial transactions.

Known as an innovation powerhouse that excels in AI, cloud and digital, NiCE is consistently recognized as the market leader in its domains, with over 8,500 employees across 30+ countries.

NiCE is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, age, sex, marital status, ancestry, neurotype, physical or mental disability, veteran status, gender identity, sexual orientation or any other category protected by law.