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Seeq

Time-series analytics platform for manufacturing

Director of Professional Services

Implementation & Technical Account ManagementPosted on Nov 11
Full-time€130k

About the Job

Requirements

  • At least 10 years in Professional Services or Consulting for enterprise SaaS, industrial software, or AI, including at least 5 years leading multi-region or global delivery teams.
  • Proven ownership of a Services Division with consistent achievement of revenue, margin, utilization, and delivery key performance indicators.
  • Deep experience designing and governing complex delivery programs in process manufacturing, including repeatable offerings that take analytics and AI-enabled solutions from use-case discovery through implementation, adoption, and scale.
  • Strong familiarity with process and operational technology data and control layers, including data historians, distributed control systems/supervisory control and data acquisition, manufacturing execution systems/laboratory information management systems, and batch records.
  • Expertise in scoping and statements of work, sales, pricing, change control, and project accounting for greenfield and brownfield plants across on-premises, hybrid (including air-gapped), and cloud deployments.
  • Operational rigor with professional services automation/customer relationship management and project accounting tools, and a data-driven approach to resourcing, pricing, and portfolio management.
  • Strong cross-functional leadership with Sales, Customer Success, Support, Product, and Finance, and executive presence with operations, engineering, IT/OT security, and quality/compliance stakeholders.
  • Experience leading delivery of AI-enabled, advanced analytics, or agentic solutions for enterprise customers, ideally in process manufacturing or other complex industrial environments.
  • Recruiting, coaching, succession planning, and building inclusive, high-performance teams across time zones.

Responsibilities

  • Own the EMEA Professional Services strategy, operating model, sales, and profit and loss, including bookings, revenue, margins, and cash flow, and deliver predictable quarterly performance.
  • Build and scale an EMEA Professional Services organization spanning implementation, solution architecture, data engineering, AI engineering, and project/program management.
  • Establish standardized delivery methodologies and packaged offerings tailored to process industries, connecting each engagement to customer-defined operational and business measures of success.
  • Drive forecasting and capacity planning for hiring, subcontractors, and partners, optimizing utilization, realization, attach rate, rates, and delivery mix.
  • Partner with Sales and Solutions Consulting on scoping, statements of work, pricing, and deal reviews to improve win rates and deal quality while reducing delivery risk for fixed-fee and time-and-materials engagements.
  • Drive demand for EMEA Professional Services through collaboration with Sales and Customer Success teams.
  • Collaborate with Customer Success, Support, and Product to ensure seamless handoffs, measurable adoption, and scale-out from pilot to multi-site or global rollout.
  • Build and manage a partner ecosystem of industrial systems integrators, engineering/procurement/construction partners, operational technology vendors, and regional specialists; define enablement, certifications, quality assurance, and a blended delivery model.
  • Implement and mature professional services automation, customer relationship management, and project accounting tools for visibility into pipeline, backlog, profitability, resourcing, delivery health, and outcomes.
  • Define and enforce delivery governance, including executive steering, change control, risk and issue management, escalation handling, and lessons learned, with attention to safety and operational continuity.
  • Establish practices for evaluating and validating AI-enabled solutions in their intended process-manufacturing context, including data and documentation readiness, repeatability, security and access considerations, operational fit, and clear ownership for ongoing use.
  • Launch continuous improvement and automation, including templates, accelerators, validated integrations, and migration/upgrade playbooks, to improve speed, quality, and margin.
  • Serve as executive sponsor for strategic accounts and represent Services in customer meetings, steering committees, and executive quarterly business reviews.
  • Represent Professional Services in EMEA on the Customer Success Leadership Team.
  • Help account teams connect customer priorities to practical Industrial AI use cases, articulate expected outcomes, and identify a credible path from an initial engagement to wider adoption.
  • Travel globally 25–40% for customer engagement, partner enablement, and team leadership.

Desired Qualifications

  • Experience implementing AI-enabled or agentic workflows in process manufacturing, including operational integration, evaluation, and human-review practices needed for adoption at scale.
  • Experience turning successful customer implementations into repeatable industry solutions, templates, or partner-delivered offerings.
  • Hands-on familiarity with common industrial platforms, including historians, manufacturing execution systems, advanced analytics, and machine learning, and integration with enterprise resource planning, computerized maintenance management systems, and quality management systems.
  • Working knowledge of how AI and agentic workflows are designed and introduced into operational settings, including validation, human oversight, security, reliability, and adoption considerations.
  • Familiarity with deployment of AI solutions in process-manufacturing environments.
  • Experience scaling partner-led delivery and certification programs with industrial systems integrators, engineering/procurement/construction partners, and operational technology vendors.
  • Domain breadth across upstream, midstream, and downstream oil and gas; commodity and specialty chemicals; and pharma/biotech.

About the Company

Seeq

Time-series analytics platform for manufacturing

Seeq provides a data analytics platform focused on time series data for manufacturing. It processes large streams of operational data and, using machine learning and artificial intelligence, converts them into actionable insights in near real-time, reducing data analysis from months to days. The platform is designed to be user-friendly and accessible to a wide range of roles within a company, with industry-specific, tailored solutions and a subscription-based access model. A recent Databricks partnership signals a commitment to accelerating data convergence across enterprises, further enhancing the service. Seeq differentiates itself by specializing in time series analytics for manufacturing, offering broad role accessibility, and industry-tailored solutions, rather than generic analytics tools. Its goal is to help businesses operate more efficiently, increase profitability, and improve sustainability by turning vast time series data into timely, clear insights.

Company size
201-500
Company stage
Series D
Total funding
$255.8M
Headquarters
Seattle, WA
Founded
2013

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