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.
We offer competitive compensation and benefits packages for our Team Members.
Sr. Engineer Data Science & Agentic AI
As a Data Science & Agentic AI Sr. Engineer , you will develop, design, implement, and deliver advanced data science, machine learning, and agentic AI products for all aspects of Machine Maintenance. The role creates novel predictive and prescriptive maintenance solutions, including AI agents and multi-agent workflows that can retrieve knowledge, reason over asset and maintenance data, use approved tools and APIs, and recommend or automate maintenance actions with appropriate human oversight. You will perform data wrangling, exploratory, descriptive, predictive, prescriptive, and agent-enabled analysis and visualization on both a recurring and ad hoc basis in support of the Projects Manager and the Maintenance user base. The Data Science & Agentic AI Sr. Engineer will identify new opportunities for intelligent process automation, Agentic AI, KPIs, visualizations, reports, dashboards, and decision-support products by aligning organizational insight requests with leadership’s strategic objectives.
Lead the entire data science, machine learning, and agentic AI lifecycle, from problem definition and data collection through model/agent design, deployment, monitoring, governance, and continuous improvement.
Ensure seamless integration and coordination across data pipelines, ML/DL models, LLM applications, agentic workflows, APIs, and business processes, optimizing for safety, scalability, efficiency, and business impact.
Establish robust monitoring mechanisms for deployed models and AI agents, enabling proactive identification of performance, reliability, drift, safety, cost, and governance issues.
Define and execute the overall machine learning, deep learning, and Agentic AI strategy aligned with business goals, maintenance reliability priorities, and enterprise technology standards.
Work closely with stakeholders to identify opportunities for advanced analytics, predictive modeling, AI agents, and intelligent workflow automation that improve maintenance reliability, decision quality, and operational efficiency.
Define and lead the Agentic AI roadmap for predictive maintenance, maintenance knowledge management, work-order triage, troubleshooting, root-cause analysis, and prescriptive reliability workflows.
Design, build, and deploy AI agents and multi-agent workflows using large language models (LLMs), retrieval-augmented generation (RAG), vector search, tool/function calling, workflow orchestration, and secure API integrations.
Integrate agentic workflows with CMMS/EAM, maintenance, asset, IoT, historian, PLC/SCADA, cloud, and enterprise data platforms while maintaining human-in-the-loop controls for higher-risk actions.
Establish AgentOps, LLMOps, and MLOps practices for prompt/version management, agent evaluation, observability, guardrails, traceability, cost monitoring, model drift detection, and continuous improvement.
Implement agentic AI safety, privacy, and security controls, including least-privilege access, data protection, prompt-injection mitigation, approval gates, audit trails, and responsible AI governance.
Drive large-scale data science, ML/DL, and Agentic AI projects that leverage data transformation, machine learning models, LLM applications, and intelligent workflow automation.
Develop first-class predictive maintenance tools, AI agents, and insights for customers by balancing data complexity, coding/visualization platforms, reliability requirements, risk controls, and client demands.
Automate and streamline projects, reports, maintenance workflows, and agent-enabled decision processes to increase efficiency, scalability, and adoption.
Develop alternative procedures, data products, agent tools, and processing methods to optimize data interactions, human-machine collaboration, and new insights.
Collaboration: Work closely with project management teams, IT professionals, reliability engineers, maintenance leaders, and business stakeholders to identify opportunities for AI agents, ML models, and automation to enhance maintenance execution and project management.
Documentation: Document project requirements, methodologies, architecture decisions, agent workflows, evaluation results, risks, and outcomes. Prepare technical reports, presentations, and user guides to effectively communicate AI/ML/Agentic AI solutions to stakeholders.
Research and Innovation: Stay updated with the latest advancements in AI/ML, Agentic AI, LLMs, RAG, vector search, orchestration frameworks, and industrial automation. Conduct research and experiments to explore new approaches and improve existing models and agents.
Ethical, Legal, and Responsible AI Considerations: Ensure compliance with ethical standards and legal requirements when dealing with sensitive data, privacy, bias, explainability, autonomy, human oversight, and potential misuse of AI/ML models or AI agents.
Training and Knowledge Sharing: Share expertise in AI/ML, Agentic AI, responsible automation, and insights with colleagues, stakeholders, and team members. Conduct training sessions or workshops to facilitate effective utilization of machine learning programs, AI agents, libraries, and governance practices.
Please note that this job description is not designed to contain a comprehensive list of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without prior notice.
Data Science & Agentic AI Manager is estimated to travel 10-30%
Please note this job description is not a full list of activities, duties or responsibilities required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without prior notice.
3-5 years - Experience in Industrial ML, Automation, Data Science, AI, or related fields
2-4 years - Experience with natural language processing (NLP), LLM applications, prompt engineering, or retrieval-augmented generation (RAG)
2-4 years - Experience designing or deploying Agentic AI solutions, AI agents, RAG applications, LLM-powered workflows, or intelligent automation
2-4 years - Experience with agent orchestration and LLM application frameworks or platforms such as LangChain, LlamaIndex, Microsoft Semantic Kernel, AutoGen, Azure AI Foundry, OpenAI API, or equivalent
3-5 years - Experience with Deep Learning, Computer Vision, Reinforcement Learning, or advanced predictive modeling
2-4 years - Experience with ethical, legal, privacy, security, and responsible AI considerations in machine learning and agentic AI systems
2-4 years - Experience implementing AI guardrails, prompt/agent evaluation, telemetry, human-in-the-loop review, and model or agent monitoring
- Experience may include a combination of work experience and education
5-7 years - Experience in Industrial ML, Automation, Data Science, AI, or related fields
3-5 years - Experience with natural language processing (NLP), LLM applications, prompt engineering, or retrieval-augmented generation (RAG)
3-5 years - Experience leading production Agentic AI, LLM, RAG, or multi-agent orchestration initiatives in industrial, manufacturing, maintenance, reliability, or enterprise operations environments
5-7 years - Experience with Deep Learning, Computer Vision, Reinforcement Learning, or advanced predictive modeling
3-5 years - Experience with ethical, legal, privacy, security, and responsible AI considerations in machine learning and agentic AI systems
3-5 years - Experience with AgentOps/LLMOps practices, including monitoring, evaluation, versioning, safety testing, audit trails, and cost/performance optimization
- Experience may include a combination of work experience and education
Preferred Competencies and Skills
Proficiency in Agentic AI and LLM application development, including prompt engineering, RAG, vector search/embeddings, function/tool calling, and agent workflow orchestration.
Experience with Agentic AI frameworks or platforms such as LangChain, LlamaIndex, Microsoft Semantic Kernel, AutoGen, CrewAI, Azure AI Foundry, OpenAI API, or equivalent.
Ability to design secure AI agent integrations with APIs, databases, CMMS/EAM platforms, cloud services, and industrial data sources while enforcing least-privilege access and approval gates.
Ability to evaluate and monitor AI agent performance using offline and online evaluations, trace logs, quality metrics, guardrails, human feedback, and incident response processes.
Understanding of Responsible AI, privacy, prompt-injection risks, model/tool misuse, auditability, and governance for autonomous or semi-autonomous AI agents.
Microsoft Office Applications – Word, Excel, PowerPoint, Outlook, Project, Visio, etc.
Proficiency in applied statistical skills, such as distributions, statistical testing, regression, etc.
Scripting and programming skills such as Python, SQL, JavaScript, C++, C#, or API-based integration for analytics, automation, and AI agent tool development
Basic understanding of PLC/SCADA systems such SIEMENS S7, ALLEN BRADLEY, BnR, Edge data Management, etc.
Understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, decision forests, gradient boosting, neural networks, and LLM-based approaches
Preferred experience with common data science and AI toolkits, such as R, Weka, Python, NumPy, Matplotlib, Pandas, MATLAB, Azure ML, and LLM/agent development libraries
Bachelor's Degree in Computer Science, Data Science, Artificial Intelligence, Industrial/Automation Engineering, or other related fields or equivalent experience
Master's Degree in Computer Science, Data Science, Artificial Intelligence, Industrial/Automation Engineering, or related field
Typical Compensation Range
Pay Rate Type: Salary
$111,766.36 - $159,267.07 / Yearly
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.
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Paid Time Off for holidays, sick time, and vacation time
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Paid parental and caregiver leaves
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Medical, including virtual care options
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Dental
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Vision
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401(k) with company match
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Health Savings Account with company match
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Flexible Spending Accounts
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Expanded mental wellbeing benefits including free counseling sessions for all team members and household family members
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Family Building Benefits including enhanced fertility benefits for IVF and fertility preservation plus adoption, surrogacy, and Doula reimbursements
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Income protection including Life and AD&D, short and long-term disability, critical illness and an accident plan
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Special discount programs including pet plans, pre-paid legal services, identity theft, car rental, airport parking, etc.
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Tuition reimbursement, college savings plan and scholarship opportunities
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And more!
https://careers.niagarawater.com/us/en/benefits
* *Los Angeles County applicants only** Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers, the California Fair Chance Act, and any other applicable local and state laws.
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Niagara Plant Name
CORP-MAIN