You'll need to be comfortable with ambiguity, at home where best practices don't exist yet, and quick to move on when the results point elsewhere.
How will you make an impact?
Build agentic systems and full-stack prototypes end-to-end, shipping a first version in days and learning from real use
Track the frontier (new models, agent patterns, protocols like MCP) and turn the promising ones into working prototypes rather than slideware
Design experiments that show whether a concept holds up, measured in quality, latency, cost, and user impact
Work directly with internal users, product managers, and customers to validate concepts early and iterate quickly
Turn validated prototypes into reference implementations and write-ups that product teams can build on, then hand off cleanly and move to the next bet
Give product and platform teams concrete feedback on where AI capabilities shine and where they fall short
Move between initiatives as priorities shift. What you learn on one bet compounds into the next
Have you got what it takes?
Have 4+ years building full-stack software, including things you started from nothing. We weigh what you've shipped more than years on a CV
Have shipped LLM-powered systems to production:features real users depended on, not demos or notebooks
Understand AI agents below the framework level: message arrays, tool calling, context management, prompt caching. You could build an agent loop from scratch and explain why it works
Use AI-assisted development (Claude Code, Codex, Cursor, or similar) as your default way of working, and it makes you measurably faster, not just busier
Are full-stackin practice: comfortable taking a prototype from API to demo UI on your own (our stack centers on TypeScript/Node.js and React)
Do your best work when the ground is still moving. New territory energises you more than a settled plan
Think in user problems first, solutions second
You will have an advantage if you also have
A strong eye for UX/UI: you can make a prototype feel like a product, and you notice when one lacks that eye
Experience with voice and real-time AI: streaming, speech-to-text/text-to-speech, voice-to-voice models
Open-source work on agent tooling (MCP servers, harnesses, evals)
Experience designing evaluations for AI systems
Background in conversational AI or customer-experience products
Enjoy NICE-FLEX!
At NICE, we work according to the NICE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.
- Requisition ID: 11563
- Reporting into: Manager, Engineering, AI Innovation
- Role Type: Individual Contributor
#LI Hybrid
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.
