Lead Solution Architect – Digital Solutions

Position Summary

Ecolab Digital develops connected, data-driven and AI-enabled solutions that improve customer operations, quality, compliance and decision-making. The Lead Solution Architect – Digital Solutions will provide hands-on, end-to-end architecture leadership for enterprise digital products and regulated operational workflows, working closely with Product, Engineering, Quality, Data & AI, shared-platform and enterprise technology teams.

The role will initially focus on digital capabilities for regulated manufacturing and pharmaceutical operations, including electronic logbooks, guided/batch execution, cleaning validation and evidence workflows, together with AI-enabled inspection and edge/cloud solutions. The architect will independently drive bounded solution decisions from business intent through engineering-ready designs, within the portfolio architecture direction established by the Senior Director, Solution Architecture. The position remains part of a centrally managed Digital Solutions Architecture team.

Key Responsibilities

• Own solution architecture for digital products and operational workflows, translating business, Product and intended-use requirements into implementable end-to-end designs.
• Architect modular digital workflow capabilities such as electronic logbooks, guided or batch execution, cleaning validation, exception handling, evidence capture, review and approval, with clear integration and data boundaries.
• Embed regulated-system needs into designs, including audit trails, electronic records/signatures where applicable, role-based access, data integrity, traceability, retention, controlled change and validation evidence; partner with Quality on control interpretation and acceptance.
• Define clean interfaces among enterprise digital platforms, shared identity/user services, domain applications, APIs/events, data services and operational systems; prioritize reuse and avoid duplicating enterprise capabilities.
• Partner closely with Engineering to establish architecture decision records, component boundaries, interface contracts, non-functional requirements, deployment patterns and engineering-ready solution guidance.
• Architect cloud-native and hybrid solutions spanning applications, event-driven integration, containerized services, data platforms and, where needed, customer-site edge processing with intermittent connectivity.
• Evaluate production AI/ML capabilities - including computer vision and inference - through clear service boundaries, model lifecycle, human review, decision traceability, monitoring and integration into trusted operational workflows.
• For edge-enabled use cases, define connectivity, local buffering/offline behavior, remote deployment and update, rollback, security, observability and recovery responsibilities across edge and cloud.
• Work with Product, Quality, Engineering and business stakeholders to distinguish product requirements, architecture decisions, validation responsibilities and delivery ownership.
• Assess build/reuse/buy and partner proposals; validate architecture assumptions, technical feasibility, delivery dependencies and alignment to Ecolab enterprise patterns without ceding architecture decision rights.
• Guide solution implementation and technical validation, surface architecture risks early, and support design decisions through release readiness and operational handover without taking on project management accountability.
• Contribute reusable patterns, reference designs and architecture decisions to the broader Digital Solutions portfolio; communicate trade-offs clearly to senior stakeholders and globally distributed teams.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering or a related technical discipline.
• 15+ years of progressive technology experience, including at least 5 years in solution/technical architecture or comparable technical leadership roles.
• Demonstrated ability to independently architect complex enterprise digital solutions across application, integration, data, cloud and platform boundaries, and translate designs into executable engineering direction.
• Experience with regulated manufacturing, pharmaceutical, quality-controlled or similarly governed operational environments; practical understanding of GxP/GMP-style controls, auditability, traceability, data integrity and controlled change.
• Experience designing enterprise workflow or transactional applications with role-based access, review/approval, exception handling, evidence capture and integration to operational systems.
• Strong cloud and distributed-systems architecture experience, including APIs/microservices, event-driven patterns, secure integration, data services, containerized workloads and resilient application design.
• Ability to design security, identity/authorization, data protection, availability, scalability, observability, supportability and disaster-recovery requirements into production solutions.
• Practical understanding of production AI/ML integration, including model/service boundaries, data governance, monitoring, quality controls and human accountability; not necessarily hands-on model development.
• Ability to work effectively with Product, Engineering, Quality, Data & AI, cybersecurity, infrastructure, enterprise-platform teams and external technology partners.
• Strong architecture judgment: can make bounded day-to-day solution decisions independently and escalate cross-platform, enterprise or material regulatory decisions with clear options and trade-offs.
• Excellent written and verbal communication, including the ability to explain architecture decisions to both technical and non-technical stakeholders in globally distributed teams.

Preferred Qualifications

• Experience in pharmaceutical manufacturing, biotechnology, medical devices, cleanrooms or other regulated production environments.
• Working knowledge of 21 CFR Part 11, EU Annex 11, ALCOA+ principles, computer system validation/assurance and associated evidence expectations.
• Architecture experience with electronic logbooks, electronic batch records/execution, cleaning validation, eQMS, MES, LIMS or related digital manufacturing/quality systems.
• Hybrid edge/cloud and connected-site architecture, including camera/video systems, GPU inference, offline operation, remote fleet management or secure edge deployment.
• Experience with computer vision, AI-assisted inspection, MLOps/model lifecycle, human-in-the-loop workflows or AI governance in production.
• Experience with Azure, AWS, Databricks or equivalent enterprise cloud/data platforms, with a platform-agnostic architecture mindset.
• Experience modernizing legacy systems and defining reusable enterprise platform/service boundaries during phased coexistence and migration.
• Experience reviewing vendor-led solution proposals, technical proofs of concept, deployment readiness and integration/validation dependencies.