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Key Responsibility Areas:
• Design, drive, and maintain end-to-end hybrid architectures for a use case that spans on-prem IT systems, manufacturing OT environments (MES, SCADA, Historians, LIMS), and Azure cloud services, ensuring consistent patterns for ingestion, processing, orchestration, and AI/ML/GenAI workloads.
• Define API-led, event-driven, and data-pipeline-driven integration patterns, including canonical models, schema/version management, and service orchestration
• Architect data and system interoperability between cloud systems and plant-floor OT environments to support Manufacturing IIoT use cases
• Develop reusable integration templates, SDKs, reference components, and platform services for AI squads to leverage across multiple use cases
• Work closely with product owners, data engineers, MLOps engineers, and application developers to translate business and AI requirements into robust solution designs
• Guide teams on best practices for API gateways, integration middleware, event streaming, data ingestion patterns, microservices, and edge/IIoT connectivity
• Define and govern Build vs Buy, SaaS selection, and best-of-breed/platform evaluations for integration middleware, vector DBs, AI orchestration layers, and IIoT connectivity components.
• Own the lifecycle of solution architecture blueprints — driving updates, modernization plans, integration roadmap alignment, and continuous improvement as new AI and OT capabilities evolve.
• Conduct solution design reviews and ensure alignment with enterprise architecture guardrails, security requirements, and platform strategy set by the Architecture Lead
• Lead and coordinate external vendors, solution delivery partners, and internal engineering squads, ensuring aligned delivery plans, architecture governance, sprint commitments, risk reporting, and transparent communication with IT, OT, cloud, and business stakeholders
• Define and enforce non-functional requirements (NFRs) covering performance, reliability, scalability, security, and observability
• Ensure architecture and integrations comply with GxP, HIPAA, GDPR, and pharma data integrity and auditability requirements
• Establish integration observability standards, including logging, tracing, correlation IDs, and operational readiness for platform services
• Collaborate with enterprise IT, manufacturing, cybersecurity, and cloud teams to ensure seamless alignment across IT/OT and hybrid environments
• Create architectural documentation, decision records, and design patterns to support governance and improve technical consistency across AI squads
• Mentor engineering teams and vendor partners, driving adoption of best practices across AI platform builds and integration workstreams.
Experience and Skills Required
• 10+ years of experience in in enterprise IT, cloud, or digital engineering roles with 5+ years in designing and delivering enterprise-scale solution architectures, spanning cloud, on-prem, enterprise applications, and manufacturing IT/OT systems.
• 2+ years of experience specifically working with AI/ML/GenAI, data platforms, RAG systems, or event-driven architectures in enterprise environments
• Strong hands-on expertise in API gateways, ESB/iPaaS platforms, event streaming (Kafka), ETL/ELT/CDC, and distributed integration patterns (reference architecture skills aligned with industry best practices).
• Deep experience integrating SAP (ECC/S4, PI/PO, BTP), Salesforce, UNS, MES, LIMS, and other OT/plant-floor systems.
• Strong IT/OT convergence expertise, including IIoT architectures, industrial protocols (OPC UA, MQTT), edge connectivity, and shop-floor data ingestion.
• Deep understanding of Industrial IoT (IIoT) ecosystems, including connectivity standards, edge architectures, and data ingestion
• Proficiency with Azure cloud services—Azure Integration Services, API Management, Event Hub, Service Bus, Logic Apps, Functions, Data Factory, Key Vault.
• Strong understanding of data platform design including lakehouse architectures, real-time/streaming data, and structured/unstructured data integration.
• Experience with security, IAM, secrets management, and compliance-aligned architecture for regulated environments (GxP, HIPAA, GDPR).
• Skilled in observability tools (Grafana, Prometheus, Datadog, Splunk) and applying tracing/logging standards across distributed integration flows.
• Experience with DevOps and CI/CD tools: GitHub Actions, GitLab CI, Jenkins; IaC with Terraform.
• Knowledge of agile development methodologies and enterprise-scale engineering practices
• Experience with pharma, life sciences, or manufacturing systems and regulatory expectations for validated environments.
• Excellent communication and stakeholder management skills across global/multi-location setting, with the ability to engage both technical and non-technical audiences, and to explain and discuss approaches and technicalities of solutions with stakeholders across multiple business functions
• Proven experience in leading external teams, managing partners and internal stakeholders
• Preferred Certifications: TOGAF, Zachman, or other EA certifications; Azure Solutions Architect Expert (highly preferred); Kubernetes (CKA/CKAD) or equivalent (nice-to-have); IIoT, OT security, or industrial connectivity certifications (preferred)
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