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.
We are seeking a highly skilled Builder to design and implement AI-driven solutions that scale across cloud data lakes. This role will collaborate closely with engineering and data teams to prototype and productionize data solutions at scale that include document and vector search, and semantic retrieval. This role will advise engineering leadership on technology selection and direction, while ensuring robust, scalable, and well-governed production deployments. This is a hands on role with significant architecture, code contribution and mentoring other builders
Key Responsibilities
- Design and implement AI-driven data solutions that scale across cloud data platforms such as Snowflake or Databricks or BigQuery (anyone one of these)
- Prototype and productionize LLM-based systems for dynamic SQL generation, document search, and semantic retrieval
- Build and maintain vector search capabilities using OpenSearch or similar technologies
- Develop metadata and data catalog layers to enable LLM reasoning and discoverability
- Build reliable, performant, and well-governed data pipelines for AI workloads
- Advise engineering leadership on technology selection and strategic direction aligned with company needs
- Partner with global engineering teams to deliver high-quality AI data solutions in production
- Experience in making Data ready for AI with Semantic layer (Nice to have)
Required Technical Background
- Expertise in large-scale cloud data platforms (Snowflake or Databricks or BigQuery, or equivalent)
- Hands-on experience building LLM-driven workflows for dynamic SQL generation or intelligent data access
- Proficiency in Python and/or Java for AI pipeline development
- Experience with vector search and OpenSearch (or similar) for document and semantic retrieval
- Familiarity with data cataloging or metadata systems such as custom YAML schemas, Atlan, or DataHub
- Strong troubleshooting and debugging skills in production environments.
- High ownership, critical thinking, curiosity, and execution skills with a collaborative mindset for working across global teams
Preferred Qualifications
- Prior experience advising engineering leadership on well-rounded technology selection and direction along with tradeoffs
- Demonstrated ability to design and implement enterprise-grade AI and data solutions.
- Strong learning orientation and enthusiasm for emerging AI and data engineering technologies.
- Ability to work independently and drive execution across distributed teams.
Experience
8 to 12 years in software or Software Engineering, Data Engineering including recent hands-on work with AI systems
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.
Skills Required
- 8 to 12 years in software or software engineering/data engineering with recent hands-on AI systems experience
- Expertise in large-scale cloud data platforms (Snowflake, Databricks, or BigQuery)
- Hands-on experience building LLM-driven workflows for dynamic SQL generation or intelligent data access
- Proficiency in Python and/or Java for AI pipeline development
- Experience with vector search and OpenSearch (or similar) for document and semantic retrieval
- Familiarity with data cataloging or metadata systems (custom YAML schemas, Atlan, DataHub)
- Strong troubleshooting and debugging skills in production environments
- High ownership, critical thinking, curiosity, and collaborative mindset for working across global teams
- Experience advising engineering leadership on technology selection and tradeoffs
- Demonstrated ability to design and implement enterprise-grade AI and data solutions
- Experience making data ready for AI with a semantic layer
- Ability to work independently and drive execution across distributed teams
NICE Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NICE and has not been reviewed or approved by NICE.
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Healthcare Strength — Benefits are described as broad and comprehensive, spanning medical, dental, vision, life, disability, and mental-health support. Added programs like FSA options and fitness stipends contribute to a well-rounded health and wellness offering.
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Retirement Support — A 401(k) is part of the package, sometimes paired with match details that are described as typical to stronger depending on role and time period. Employee stock participation is also positioned as an additional long-term wealth-building component for eligible roles.
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Flexible Benefits — Flexible work arrangements are emphasized, including hybrid setups and remote options for some roles. Flex scheduling, paid holidays, and paid sick time add to the perceived flexibility of the overall rewards package.
NICE Insights
What We Do
NICE (Nasdaq: NICE) is the worldwide leading provider of both cloud and on-premises enterprise software solutions that empower organizations to make smarter decisions based on advanced analytics of structured and unstructured data. NICE helps organizations of all sizes deliver better customer service, ensure compliance, combat fraud and safeguard citizens. Over 25,000 organizations in more than 150 countries, including over 85 of the Fortune 100 companies, are using NICE solutions. www.nice.com.
