Senior AI Software Engineer

NICE•Sandy, UT

About The Position

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. 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.

Requirements

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 Haves

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)

Responsibilities

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
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