Note: The job is a remote job and is open to candidates in USA. Seeq Corporation is a remote-first company focused on providing advanced analytics and decision intelligence software for industrial process data. The AI Applications Engineer will design, build, and deliver production-grade agentic AI solutions on the Seeq platform while leading end-to-end implementations and collaborating with various teams to enhance customer experience and operational efficiency.
Responsibilities
• Author scalable AI agents utilizing that extend and orchestrate Agent Q for repeatable, multi-step industrial workflows (e.g., AI-generated operational reports, batch deviation analysis, root cause investigations, condition-monitor-driven investigations)
• Build custom AI agents outside of Seeq to interface applications in the broader industrial technology stack with Agent Q and Seeq’s AI platform
• Design and implement Skills and Code Tools in Python (Seeq Data Lab, SPy library) that give agents reliable, governed access to enterprise systems — CMMS, historians, document stores, and customer-built AI services
• Build solution components (accelerators, templates, calculators, KPIs, dashboards, condition monitors, Vantage Rooms) in Seeq Workbench, Organizer, Vantage, and Data Lab that the agent layer can act on and reason about
• Package agentic solutions for reuse with documented prompts/instructions, journals, example datasets, validation plans, and success criteria ready for partner and customer delivery
• Configure Agent Extensibility to wire Seeq Intelligence into customer ecosystems (CMMS, integrity tools, MES, Power BI/Teams, Microsoft Copilot, Snowflake, Databricks)
• Write production-quality Python for agent Skills, Data Lab notebooks, scheduled/event-triggered workflows; apply modern software engineering practices (version control, code review, testing, CI/CD where applicable)
• Author and consume REST/HTTPS APIs for third-party AI agents and enterprise systems; manage authentication patterns (SSO, delegated permissions, SAS URIs) for governed agent access
• Connect solutions to enterprise data ecosystems and downstream tools (e.g., OPC UA/OPC HDA; AVEVA PI/PI AF; SQL databases, data lakes/warehouses; Databricks; Azure ML; AWS Lambda; Power BI/Tableau; Microsoft 365 / SharePoint) following security, scalability, and performance best practices
• Apply prompt engineering, agent instruction design, and evaluation techniques to make agent behavior consistent, trustworthy, and reproducible at an industrial scale
• Partner with the Software Team, Industry Principals, Product Management, and Revenue Teams to align Intelligence solutions to roadmap and close capability gaps
• Support Product Marketing, Solution Consulting, and Sales with credible Intelligence demos, narratives, and GTM assets; assist targeted pre-sales engagements where agentic solution expertise is required
• Create enablement kits (deployment guides, reference architectures, agent design playbooks, sample Skills/notebooks) and mentor Seeq partners and customer champions to scale agentic delivery globally
• Coach customer subject matter experts on encoding their expert reasoning into agent instructions, journals, and custom agent workflows so institutional knowledge becomes shareable and operational
• Gather field feedback, monitor agent adoption and quality, and iterate on solution reliability, trustworthiness, and learnability; contribute reusable agent patterns into Seeq’s solution library and training content
Skills
• Design, build, and deliver production-grade agentic AI solutions on the Seeq platform
• Lead end-to-end Seeq Intelligence implementations
• Author scalable AI agents utilizing Agent Q for repeatable, multi-step industrial workflows
• Build custom AI agents outside of Seeq to interface applications in the broader industrial technology stack
• Design and implement Skills and Code Tools in Python (Seeq Data Lab, SPy library)
• Build solution components in Seeq Workbench, Organizer, Vantage, and Data Lab
• Package agentic solutions for reuse with documented prompts/instructions, journals, example datasets, validation plans, and success criteria
• Configure Agent Extensibility to wire Seeq Intelligence into customer ecosystems
• Write production-quality Python for agent Skills, Data Lab notebooks, scheduled/event-triggered workflows
• Author and consume REST/HTTPS APIs for third-party AI agents and enterprise systems
• Connect solutions to enterprise data ecosystems and downstream tools
• Apply prompt engineering, agent instruction design, and evaluation techniques
• Partner with the Software Team, Industry Principals, Product Management, and Revenue Teams
• Support Product Marketing, Solution Consulting, and Sales with credible Intelligence d