AI Application Engineer, EMEA

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

The essential functions include, but are not limited to, the following: Design and Build Agentic AI Solutions

· 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).

Software Engineering and Architecture

· 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 industrial scale. Collaborate Cross-Functionally

· 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. Enable Customers and Partners

· 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. Continuous Improvement

· 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.

· Software development proficiency in Python, including writing maintainable code, packaging, working with REST APIs, and using libraries such as Pandas; familiarity with modern 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, including prompt engineering, tool/skill design, and handling multi-step reasoning.

· Process manufacturing experience in O&G, Chemicals, Pharma, Power, Pulp & Paper, Food & Beverage, Semiconductor, or related industries; ability to translate operational objectives into analytics-driven and agent-driven workflows.

· Time series analytics proficiency, including feature engineering, event/condition detection, asset segmentation, anomaly/quality logic, 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 building solutions in Seeq Workbench, Organizer, Vantage, and Data Lab.

· Customer-facing delivery experience leading pilots/POCs to production; strong value articulation, scope management, and cross-functional alignment.

· Education: Bachelor’s degree (or higher) in Computer Science, Software Engineering, Chemical, Mechanical, Electrical, Industrial, or Systems Engineering, Applied Math, Data Analytics, or related discipline - or equivalent relevant experience.

· 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 to enable closed-loop, anomaly-to-action workflows.

· Familiarity with the Process Manufacturing Industry-specific, including Oil & Gas, Pharmaceuticals, Power, Mining, etc.

· Familiarity with cloud/data platforms and modern industrial data architectures (Azure/AWS/GCP, Databricks, Snowflake, Historians).

· Experience with software engineering practices: Git, code review, unit testing, CI/CD, containerization, observability/logging, and secure handling of credentials.

· Strong technical communication across SME, manager, and executive audiences; proven in demos, workshops, and AI solution storytelling.

The employee is regularly required to communicate effectively, work with digital tools, and collaborate across time zones in a remote environment; occasional travel to customer sites, partner locations, or events may be required (typically 20-40%, varying by project portfolio).

Salary - 101,790 GBP

• Unlimited PTO
• Internet and mobile phone reimbursements
• Vacation bonus program
• Generous home office allowance
• The best co-workers (we’ve analyzed the data, so we know it’s true.)
• Pet-friendly workspace (your dog will be so happy to have you home)
• You love your job!