Lead Solution Architect – Digital Solutions

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 capabilitiesincluding computer vision and inferencethrough 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

Bachelors 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.