AI Applications Engineer

Seeq

3d•$165,000 - $185,000•Remote

About The Position

The AI Applications Engineer designs, builds, and delivers production-grade agentic AI solutions on the Seeq platform to accelerate time-to-value for process manufacturers (O&G, Chemicals, Pharma, Power, Pulp & Paper, Food & Beverage, Semiconductor, and related industries). This role pairs the customer-facing solution engineering responsibilities of an Applications Engineer with deeper software engineering skills focused on building, extending, and operationalizing custom AI agents that interface with Agent Q, Seeq’s advanced agentic AI Analyst, along with Agent Builder, Document Access, and Agent Extensibility capabilities. The AI Applications Engineer leads end-to-end Seeq Intelligence implementations — from use case discovery and solution architecture, through Python-based agent and Skill development, to enablement and lifecycle ownership. Typical solution patterns include anomaly-to-action workflows that integrate with Industrial Software technologies (historian, CMMS, APM, etc), Microsoft Copilot integrations, AI-generated operational reporting, and customer internal documentation and SME knowledge. Seeq builds advanced analytics and decision intelligence software for industrial process data and operates as a remote-first company with a strong culture of collaboration and iteration.

Requirements

Production-grade Python for agent Skills, Data Lab notebooks, scheduled/event-triggered workflows
Modern software engineering practices (version control, code review, testing, CI/CD where applicable)
REST/HTTPS APIs for third-party AI agents and enterprise systems
Authentication patterns (SSO, delegated permissions, SAS URIs) for governed agent access
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)
Prompt engineering, agent instruction design, and evaluation techniques
Experience with Seeq platform (Agent Q, Agent Builder, Document Access, Agent Extensibility, Seeq Data Lab, SPy library, Seeq Workbench, Organizer, Vantage)
Experience with industrial software technologies (historian, CMMS, APM, MES)
Experience with Microsoft Copilot integrations
Experience with AI-generated operational reporting
Experience with customer internal documentation and SME knowledge
Authorization to work in the country of residence
Not seeking US F1 or H-1B visa sponsorship

Nice To Haves

Experience with O&G, Chemicals, Pharma, Power, Pulp & Paper, Food & Beverage, Semiconductor industries

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.