AI Application Engineer, EMEA - Seeq

About the Role

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 customer-facing solution engineering 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.

You will lead 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 integrated with Industrial Software technologies, Microsoft Copilot integrations, AI-generated operational reporting, and customer internal documentation and SME knowledge.

Responsibilities

Design and Build Agentic AI Solutions

• Author scalable AI agents extending and orchestrating Agent Q for repeatable, multi-step industrial workflows (e.g., AI-generated operational reports, batch deviation analysis, root cause 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).
• Build solution components (accelerators, templates, calculators, KPIs, dashboards, condition monitors) in Seeq Workbench, Organizer, Vantage, and Data Lab.
• Package agentic solutions for reuse with documented prompts, instructions, journals, example datasets, and validation plans.
• Configure Agent Extensibility to wire Seeq Intelligence into customer ecosystems (CMMS, MES, Power BI/Teams, Microsoft Copilot, Snowflake, Databricks).

Software Engineering and Architecture

• Write production-quality Python for agent Skills, Data Lab notebooks, and event-triggered workflows using modern software engineering practices.
• Author and consume REST/HTTPS APIs for third-party AI agents and enterprise systems, managing authentication patterns.
• Connect solutions to enterprise data ecosystems (OPC UA, AVEVA PI, SQL databases, data lakes, Azure ML, AWS Lambda, Power BI, SharePoint) following security and performance best practices.
• Apply prompt engineering, agent instruction design, and evaluation techniques to ensure consistent, trustworthy agent behavior at industrial scale.

Collaborate Cross-Functionally

• Partner with the Software Team, Industry Principals, Product Management, and Revenue Teams to align Intelligence solutions to roadmap.
• Support Product Marketing, Solution Consulting, and Sales with credible Intelligence demos, narratives, and GTM assets.

Enable Customers and Partners

• Create enablement kits (deployment guides, reference architectures, agent design playbooks, sample Skills) and mentor Seeq partners and customer champions.
• Coach customer subject matter experts on encoding their expert reasoning into agent instructions, journals, and Custom Agent workflows.

Continuous Improvement

• Gather field feedback, monitor agent adoption and quality, and iterate on solution reliability and trustworthiness.

Requirements

• Software development proficiency in Python, including packaging, REST APIs, and Pandas; familiarity with AI/LLM tooling concepts (prompts, tool/function calling, retrieval, evaluation, agent orchestration).
• Agentic AI experience: hands-on experience designing, building, and deploying AI agents or LLM-powered workflows.
• Process manufacturing experience in O&G, Chemicals, Pharma, Power, Pulp & Paper, Food & Beverage, Semiconductor, or related industries.
• Time series analytics proficiency, including feature engineering, event/condition detection, asset segmentation, and KPI design.
• Historian and OT data experience with platforms such as AVEVA PI, IP.21, DeltaV, Wonderware, Canary, or GE Proficy.
• Hands-on Seeq skills, including Seeq Workbench, Organizer, Vantage, and Data Lab.
• Customer-facing delivery experience leading pilots/POCs to production.
• Education: Bachelor’s degree (or higher) in Computer Science, Software Engineering, Engineering, Applied Math, Data Analytics, or related discipline — or equivalent experience.

Preferred Qualifications

• Experience integrating AI agents with Microsoft Copilot / Copilot Studio, SharePoint knowledge sources, Power Platform, or Microsoft Fabric.
• Experience integrating with CMMS systems (e.g., IBM Maximo) and other enterprise systems via APIs.
• Familiarity with cloud/data platforms and modern industrial data architectures (Azure/AWS/GCP, Databricks, Snowflake).
• Experience with software engineering practices: Git, code review, unit testing, CI/CD, containerization, and observability.

Benefits

• Unlimited PTO
• Internet and mobile phone reimbursements
• Vacation bonus program
• Generous home office allowance
• Pet-friendly workspace