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Principal Data Scientist - Gen AI & Agentic AINiagara Bottling • Diamond Bar, California, United States
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Principal Data Scientist - Gen AI & Agentic AI

Niagara Bottling
  • US
    Diamond Bar, California, United States
  • US
    Diamond Bar, California, United States
Apply Now

About

At Niagara, we’re looking for Team Members who want to be part of achieving our mission to provide our customers the highest quality most affordable bottled water. Consider Applying Here, If You Want To:
Work in an entrepreneurial and dynamic environment with a chance to make an impact. Develop lasting relationships with great people. Have the opportunity to build a satisfying career.
Principal Data Scientist – Gen AI & Agentic AI The Principal Scientist leads other scientists and engineers on Research & Development (R&D) initiatives in materials, design, and process. Focuses on long‑term team and business growth. Strategizes, guides and performs innovative research. Interacts with other team members and teams to create new products and systems, improves line efficiency, quality, or enables other projects which add value to Niagara’s core business or aids in creating new business directions. Essential Functions
Lead the strategy, design, and delivery of enterprise‑grade GenAI and agentic AI solutions, driving the development of next‑generation agents, LLM‑powered applications, and hybrid GenAI/ML systems that improve decision‑making, automation, and operational efficiency across Niagara’s business units. Partner with senior business leaders, product management, and cross‑functional technology teams to translate ambiguous or complex business challenges into clear problem statements, measurable outcomes, and prioritized AI initiatives. Architect robust agentic systems, including multi‑step orchestration, tool‑use agents, retrieval‑augmented workflows, grounding layers, and guardrail frameworks that ensure reliability, safety, and domain accuracy. Design and implement scalable analytic and modeling approaches, including feature engineering, embedding strategies, retrieval pipelines, fine‑tuning, prompt engineering, supervised learning, and hybrid architectures combining classical ML with GenAI capabilities. Develop, prototype, and operationalize LLM‑driven solutions using enterprise platforms such as Azure OpenAI, Databricks, Snowflake Cortex, Oracle AI Agent Studio, and containerized microservices. Build reusable, interpretable, and production‑ready models, agents, and pipelines, ensuring they meet standards for scalability, observability, resilience, and maintainability. Establish and own Niagara’s LLMOps and agent lifecycle practices, including CI/CD for models and agents, monitoring, evaluation frameworks, prompt testing, drift detection, and continuous improvement workflows. Champion Responsible AI principles, embedding safety, fairness, explainability, privacy, security, grounding, and governance throughout the agent and model development lifecycle. Define technical standards and best practices for GenAI development, including vector database usage, evaluation frameworks, embeddings, data preparation workflows, and content grounding strategies. Collaborate with IT, data engineering, and platform teams to ensure required infrastructure—data access, compute environments, vector stores, APIs, and application integration layers—is in place for scalable deployment. Influence executive stakeholders by crafting compelling narratives, visualizations, and recommendations that communicate complex AI concepts in business‑relevant terms and drive strategic alignment. Coach, mentor, and uplift the technical capabilities of data scientists and senior individual contributors, providing thought leadership, code reviews, architectural guidance, and development plans. Drive innovation initiatives and proofs‑of‑concept, evaluating emerging GenAI frameworks, agent orchestration tools, evaluation stacks, retrieval technologies, and model families. Contribute to enterprise AI governance, including model/agent documentation, risk assessments, access control, versioning, testing standards, and audit readiness. Foster cross‑functional collaboration, identifying opportunities to leverage GenAI across manufacturing, supply chain, commercial operations, HR, legal, and corporate functions. Represent DDI as a subject‑matter expert for GenAI and agentic AI, sharing insights, educating stakeholders, and building organizational readiness for advanced AI capabilities. Analytics Product Expertise: Strong knowledge of agile analytics product delivery, full‑stack development (Data Engineering, Data Science, UX/UI), and industry best practices. Product & Project Management: Skilled in developing Product Briefs, managing roadmaps, backlog prioritization, release planning, sprint metrics, and cross‑team coordination while ensuring business value‑driven outcomes. Business & Process Understanding: Deep comprehension of business processes, functional digital capabilities (Supply Chain, Manufacturing, Finance, Sales & Marketing), and high‑quality analytics delivery. Change & People Management: Skilled in managing change initiatives, fostering collaboration, and balancing competing priorities in a fast‑paced environment.
Qualifications
Minimum Qualifications:
10+ years of experience in Data Science or Analytics, including 4+ years leading projects or technical teams. Deep expertise in Machine Learning, Generative AI, Large Language Models (LLMs), Retrieval‑Augmented Generation (RAG), and agentic AI systems. Demonstrated experience designing and delivering production AI systems using Azure and Databricks. Strong storytelling, executive communication, and influence skills, with an ability to translate complex AI concepts into business outcomes. Experience may include a combination of work experience and education.
Preferred Qualifications:
12–15+ years of experience in Data Science, AI/ML engineering, or advanced analytics, including leading platform‑level or enterprise GenAI programs. Experience working with agent orchestration frameworks, vector databases, evaluation stacks, and modern LLMOps tooling. Experience with Oracle AI Agent Studio. Experience may include a combination of work experience and education.
Competencies
Strategy & Technical Leadership – Ability to define enterprise AI strategy, set technical direction for GenAI and agentic AI programs, and guide long‑term architectural decisions. Architecture & Delivery Excellence – Expertise in designing end‑to‑end agentic systems, retrieval pipelines, and LLM‑powered applications with strong standards for scalability, reliability, and security. LLMOps & Governance – Deep understanding of model/agent lifecycle management, evaluation frameworks, monitoring, guardrails, Responsible AI principles, and enterprise governance processes. Stakeholder Influence – Strong capability to communicate complex AI concepts to executive audiences, drive alignment across product and business teams, and influence cross‑functional decisions. People Leadership – Demonstrated ability to coach and develop data scientists and senior ICs, elevate technical maturity, and foster a culture of innovation and high performance. Advanced GenAI & Agentic System Design – Expertise in LLMs, RAG, embeddings, vector databases, agent frameworks, and multi‑step orchestration patterns. AI Solution Delivery & Integration – Experience integrating models and agents into applications, microservices, or enterprise platforms (Azure, Databricks, Snowflake, Oracle AI Agent Studio). Analytical & Systems Thinking – Strong ability to break down ambiguous problems, synthesize complex information, and design solutions that balance technical depth with business impact. Cross‑Functional Collaboration – Proven ability to work effectively with product, engineering, IT, operations, and business stakeholders to unlock enterprise‑wide value. Executive Communication & Storytelling – Skilled at creating compelling narratives, visualizations, and recommendations that drive strategic decisions.
Education
Minimum Required:
Bachelor's Degree in Computer Science/Data Science/Statistics or other related field.
Preferred:
Master’s Degree in Computer Science/Data Science/Statistics or other related field.
Certification/License
Required: N/A Preferred: Agentic AI / Gen AI / Machine Learning or Advanced Analytics certifications.
Typical Compensation Range Pay Rate Type: Salary $149,915.38 - $217,377.31 / Yearly Bonus Target: 15% Annual Benefits Our Total Rewards package is thoughtfully designed to support both you and your family. Regular full‑time team members are offered a comprehensive benefits package, while part‑time, intern, and seasonal team members are offered a limited benefits package.
Paid Time Off for holidays, sick time, and vacation time Paid parental and caregiver leaves Medical, including virtual care options Dental Vision 401(k) with company match Health Savings Account with company match Flexible Spending Accounts Expanded mental wellbeing benefits including free counseling sessions for all team members and household family members Family Building Benefits including enhanced fertility benefits for IVF and fertility preservation plus adoption, surrogacy, and Doula reimbursements Income protection including Life and AD&D, short and long‑term disability, critical illness and an accident plan Special discount programs including pet plans, pre‑paid legal services, identity theft, car rental, airport parking, etc. Tuition reimbursement, college savings plan and scholarship opportunities And more!
Benefits information available at: https://careers.niagarawater.com/us/en/benefits #J-18808-Ljbffr
  • Diamond Bar, California, United States

Languages

  • English
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