Job description

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. Overview 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.

Requirements

Must-haves

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
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
8 to 12 years in software or Software Engineering, Data Engineering including recent hands-on work with AI systems

Nice-to-haves

Experience in making Data ready for AI with Semantic layer (Nice to have)
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.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aillmsqlpythonjava

Platform: greenhouse
Effort: quick