NiCE
NiCE2 open roles

Forward Deployed Engineer

Remote, USRemoteMidFull-time

Posted 2 days ago

The role in short

Architect and deliver production-ready conversational AI agents for enterprise customers, owning the full lifecycle from pilot to launch.

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.

So, what's the role all about?

  • You'll architect and deliver production-ready conversational AI agents that sit at the core of the business and directly fuel company growth.
  • These are live, scalable agentic AI systems, not experiments or proof-of-concepts, operating across sectors like financial services, healthcare, and commerce.
  • You'll have full ownership of the entire AI agent lifecycle, steering projects from early pilot through launch and ongoing refinement.
  • You'll collaborate directly with decision-makers at the world’s leading enterprises to tackle their highest-priority challenges with agentic AI.
  • The patterns and problems you encounter in the field will feed directly into the evolution of the platform, tools, and product roadmap.

How will you make an impact?

  • Develop agentic systems (agents) for large-scale companies that measurably outperform human operators in areas like retention and churn reduction.
  • Build agents that handle nuanced, integrated customer interactions, across a range of CX transforming use cases.
  • Design reusable agent frameworks adapted to the specific demands of different industries.
  • Drive design partnerships around new product directions, including agent architectures, self-service features, and generative development workflows.
  • Push the boundaries with emerging voice models and pioneer their integration into enterprise-grade deployments.
  • Set the standard for how AI agents are constructed, evaluated, and improved in live production settings.

Have you got what it takes?

  • Hands-on experience building and operating end-to-end production systems at scale.

  • With a natural builder's mentality with high personal agency, you default to finding solutions and shipping them.

  • Startup founder or early engineer experience is highly valued, you understand the tradeoffs between speed, quality, and ownership.

  • Proven technical problem-solving ability, particularly in rapidly shifting, loosely defined environments.

  • Experience developing or operating AI/LLM-powered systems in production is a major plus.

  • Working knowledge of the current AI agent toolkit: evaluation frameworks, orchestration tooling, RAG pipelines, and prompt engineering.

  • Familiarity with React, TypeScript, and/or Go is an advantage.

  • At ease working face-to-face with customers to unpack their problems and deliver practical solutions.

  • Prior experience in customer-facing or externally-led technical roles is a plus.

  • A clear, direct communicator who can be equally persuasive with engineers and executives.

  • Comfortable operating in ambiguity and making forward progress without waiting for complete clarity.

  • Able to balance competing priorities and drive alignment across technical and business teams.

What's in it for you?

  • Build AI agents that run in production at meaningful scale, not slideware or research exercises.
  • Work shoulder-to-shoulder with leaders at globally recognized enterprises and high-growth startups.
  • Directly influence the direction of NiCE's AI agent platform through the real problems you solve.
  • Operate with genuine autonomy and end-to-end ownership across the agent lifecycle.
  • Work at the cutting edge of AI agent development with access to the latest models, infrastructure, and research.

Requisition ID: 11995

Reporting into: Director, FDE Strategy

Role Type: Individual Contributor

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.

Prep for this interview

4 questions likely to come up at NiCE, each matched to a line in this posting.

  1. 1LLMs, RAG and agents
    They wrote: “Working knowledge of the current AI agent toolkit: evaluation frameworks, orchestration tooling, RAG pipelines, and prompt engineering.”

    A customer wants a chatbot over their internal documents. How do you build it?

    How to answer

    Why they ask: RAG is the most common first project. They want the whole path, from messy files to answers people trust.

    1. Collect and clean the documents; handle permissions per user
    2. Split them into chunks, embed, and store with source links
    3. Retrieve, then answer with citations; say “I don't know” when retrieval is weak
    4. Build a test set of real questions with expected answers before launch

    Tip: Spend more time on the data and on testing than on the model.

  2. 2Coding
    They wrote: “Familiarity with React, TypeScript, and/or Go is an advantage.”

    Here's a CSV export from a customer. Write a script that cleans it and loads it into our API.

    How to answer

    Why they ask: Very close to real FDE work. They watch how you handle bad rows and failures.

    1. Read with a proper CSV parser; check the header first
    2. Validate each row and collect errors, not crash on the first one
    3. Send in batches with retries and a clear report at the end
    4. Write one or two quick tests for the parsing

    Tip: Talk through edge cases out loud: encodings, missing fields, duplicates, rate limits.

  3. 3Ownership and working with customers
    They wrote: “Operate with genuine autonomy and end-to-end ownership across the agent lifecycle.”

    Tell me about something you shipped that broke in production.

    How to answer

    Why they ask: Everyone has broken production. They want to hear you own it and change something afterwards.

    1. What broke and who it affected
    2. How you found out and what you did in the first hour
    3. The root cause, said plainly
    4. What you changed so it can't happen the same way again

    Tip: Pick a real one with a cost. Spend most of the answer on what you changed.

  4. 4Integrations and APIs
    They wrote: “Push the boundaries with emerging voice models and pioneer their integration into enterprise-grade deployments.”

    Walk me through connecting our product to a customer's internal system that has no documentation.

    How to answer

    Why they ask: This happens weekly in the job. They want a calm, step-by-step method.

    1. Find who owns the system and get read access to a test environment
    2. Watch real traffic or logs to learn the data shapes
    3. Build a thin adapter with logging around every call
    4. Agree on how failures get reported, and who fixes what

    Tip: Talk about finding the owner of the system first. The code is the easy part.

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