Niagara
Sr.EngineerDataScience&AgenticAI
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“Sr. Engineer Data Science & Agentic AI at Niagara. Skills: Agentic AI, Machine Learning, Data Science, LLM. Develop data science products. Design data science products”
Industry & Context.
Analytical; Problem-solving; Root cause analysis; Troubleshooting
What They're Looking For.
Must Have
Bachelor's Degree in Computer Science, Bachelor's Degree in Data Science, Bachelor's Degree in Artificial Intelligence, Bachelor's Degree in Industrial/Automation Engineering, Equivalent experience to Bachelor's Degree
Nice to Have
Master's Degree in Computer Science, Master's Degree in Data Science, Master's Degree in Artificial Intelligence, Master's Degree in Industrial/Automation Engineering
What You'll Do.
Develop data science products
Design data science products
Implement data science products
Deliver data science products
Implement AI products
Implement ML products
Create predictive maintenance solutions
Create prescriptive maintenance solutions
Create multi-agent workflows
Recommend maintenance actions
Automate maintenance actions
Perform data wrangling
Perform exploratory analysis
Perform descriptive analysis
Perform predictive analysis
Perform prescriptive analysis
Perform agent-enabled analysis
Perform visualization
Identify automation opportunities
Identify Agentic AI opportunities
Identify KPI opportunities
Identify visualization opportunities
Identify report opportunities
Identify dashboard opportunities
Identify decision-support opportunities
Lead data science lifecycle
Lead machine learning lifecycle
Lead agentic AI lifecycle
Coordinate data pipelines
Coordinate LLM applications
Coordinate agentic workflows
Coordinate business processes
Optimize for scalability
Optimize for efficiency
Optimize for business impact
Establish monitoring mechanisms
Identify performance issues
Identify reliability issues
Identify drift issues
Identify safety issues
Identify governance issues
Define Agentic AI strategy
Execute Agentic AI strategy
Align strategy with business goals
Align strategy with maintenance priorities
Align strategy with enterprise standards
Identify opportunities for advanced analytics
Identify opportunities for predictive modeling
Identify opportunities for AI agents
Identify opportunities for workflow automation
Define Agentic AI roadmap
Lead Agentic AI roadmap
Design multi-agent workflows
Build multi-agent workflows
Deploy multi-agent workflows
Integrate agentic workflows
Maintain human-in-the-loop controls
Establish AgentOps practices
Establish LLMOps practices
Establish MLOps practices
Manage prompt versions
Manage agent evaluations
Manage cost monitoring
Implement AI safety controls
Implement AI privacy controls
Implement AI security controls
Mitigate prompt-injection
Implement approval gates
Implement audit trails
Implement responsible AI governance
Drive data science projects
Drive Agentic AI projects
Leverage data transformation
Leverage machine learning models
Leverage LLM applications
Leverage intelligent workflow automation
Develop predictive maintenance tools
Automate maintenance workflows
Automate agent-enabled processes
Develop alternative procedures
Develop data products
Develop processing methods
Optimize data interactions
Optimize human-machine collaboration
Optimize new insights
Contribute to storyboarding
Develop recommendations
Produce leadership-quality deliverables
Manage ad hoc requests
Review ad hoc requests
Work with project management teams
Work with IT professionals
Work with reliability engineers
Work with maintenance leaders
Work with business stakeholders
Document project requirements
Document methodologies
Document architecture decisions
Document agent workflows
Document evaluation results
Prepare technical reports
Prepare presentations
Communicate AI/ML/Agentic AI solutions
Stay updated on AI/ML advancements
Stay updated on Agentic AI advancements
Stay updated on LLM advancements
Stay updated on RAG advancements
Stay updated on vector search advancements
Stay updated on orchestration frameworks
Stay updated on industrial automation
Explore new approaches
Improve existing models
Improve existing agents
Ensure compliance with ethical standards
Ensure compliance with legal requirements
Address sensitive data
Address explainability
Address human oversight
Address potential misuse of AI/ML models
Address potential misuse of AI agents
How You'll Work.
Team & Collaboration
Project management teams; IT professionals; Reliability engineers; Maintenance leaders; Business stakeholders
Communication Scope
Oral communication; Written communication; Executive presentations
Process & Methodology
Roadmap planning
Full Job Description
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. _Detailed Description_ * Full Spectrum Data Science and Agentic AI Management * 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, e
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