Solutions Engineering Lead - Hybrid Cloud/Full Stack

Sanofi • Morristown, NJ

6d • $187,500 - $270,833 • Hybrid

About The Position

Join Sanofi as our Lead Solutions Engineer to shape the future of pharmaceutical technology. Reporting to the Head of Solutions Engineering, you will serve as the technical lead for our Solutions Engineering practice and collaborate with Strategic Architecture and digital partners to drive Sanofi’s transformation into an AI-powered biopharmaceutical company. This is a full-stack engineering role that combines hands-on expertise in cloud, DevOps, containers, and AI infrastructure with strategic vision-setting. You will lead solution design discussions with Digital R&D, Manufacturing, and corporate teams, and establish technical patterns and standards to guide our global technology evolution. This is a hybrid role with 3 days a week onsite in Morristown.

Requirements

• Bachelor’s degree in computer science, Engineering, Information Technology, or related technical field - required.
• 10+ years of progressive cloud and infrastructure engineering experience - required.
• AWS certifications: Solutions Architect Professional, DevOps Engineer Professional, Machine Learning Specialty
• Azure certifications: Solutions Architect Expert, DevOps Engineer Expert, AI Engineer Associate
• Kubernetes certifications: CKA (Certified Kubernetes Administrator), CKAD (Certified Kubernetes Application Developer)
• Additional relevant certifications: Terraform Associate, TOGAF, ITIL, Agile/DevOps
• Reporting to the Head of Solutions Engineering (Technology Principal)
• Travel required for digital partner engagement and strategic initiatives.
• 10+ years in enterprise infrastructure and cloud engineering roles with increasing technical leadership
• Deep expertise in AWS and Azure with production-scale implementations
• Advanced Kubernetes experience, including EKS/AKS in enterprise pharmaceutical or regulated environments.
• Hybrid cloud architecture integrating on-premises systems with cloud-native applications.
• Infrastructure fundamentals, including networking, storage, compute, and security at enterprise scale.
• Infrastructure as Code experience with Terraform, CloudFormation, or equivalent tools at scale.
• CI/CD pipeline design, including automated testing, security scanning, and compliance validation.
• Container orchestration with production Kubernetes implementations and cloud-native patterns
• Observability platform experience, including monitoring, logging, alerting, and distributed tracing.
• Cross-functional collaboration guiding technical decisions across diverse business and technology teams.
• Standards development, creating technical patterns, and best practices adopted across organizations.
• Stakeholder communication, translating technical concepts for business leaders and non-technical audiences.
• Lead complex technical discussions with confidence and credibility across diverse stakeholder groups.
• Challenge technical assumptions constructively while respecting domain expertise.
• Balance innovation adoption with operational stability and pharmaceutical compliance.
• Make sound architectural decisions in the face of ambiguity and incomplete information.
• Connect technical solutions to pharmaceutical business outcomes and patient impact.
• Anticipate future technology trends and proactively prepare infrastructure capabilities.
• Design solutions that scale globally across diverse regulatory environments
• Balance short-term delivery needs with long-term architectural vision.
• Build trust and credibility with digital peer organizations through consistent delivery.
• Navigate matrix organizations and drive consensus without formal authority.
• Partner effectively with Enterprise Architecture while maintaining a solutions delivery focus.
• Mentor and develop engineering talent through technical guidance and knowledge sharing.
• Articulate complex technical architectures clearly for both technical and business audiences.
• Create compelling technical documentation, reference architectures, and implementation guides.
• Present technical vision and strategy to C-level executives and senior leadership
• Facilitate productive technical discussions across distributed, global teams.

Nice To Haves

• Master's degree
• Hands-on AI/ML infrastructure deployment, including model serving, training clusters, and data pipelines.
• AIOps implementation experience on AWS (CloudWatch Insights, Systems Manager, DevOps Guru, or equivalent)
• ML platform operations with experience in SageMaker, Azure ML, or similar enterprise ML platforms
• Intelligent automation, including predictive analytics, anomaly detection, and automated remediation.
• Pharmaceutical or life sciences technology implementation with GxP compliance understanding
• Regulated industry background (healthcare, financial services, government) with validation experience
• Large-scale digital transformations in organizations with 10,000+ users
• Multi-cloud governance and FinOps implementation with measurable cost optimization outcomes
• Site Reliability Engineering practices, including error budgets, SLOs, and incident management.
• Technical team leadership, including hiring, mentoring, and developing engineering talent.
• Open-source contributions to cloud-native, Kubernetes, or AI/ML infrastructure projects
• Enterprise SDLC Implementation
• Cybersecurity expertise including code security and infrastructure hardening

Responsibilities

• Design and implement hybrid cloud solutions on AWS and Azure for pharmaceutical workloads.
• Architect containerized applications using Kubernetes (EKS/AKS) with enterprise-grade reliability.
• Build Infrastructure as Code (Terraform, CloudFormation) for rapid, consistent deployments.
• Implement cloud-native patterns (microservices, serverless, and event-driven) that support pharmaceutical compliance.
• Deploy and optimize AI/ML infrastructure supporting drug discovery and manufacturing automation.
• Implement AIOps platforms for intelligent infrastructure monitoring and automated operations.
• Build data pipelines and model serving infrastructure for pharmaceutical AI applications.
• Design GPU-optimized clusters and distributed computing environments for machine learning workloads.
• Implement CI/CD pipelines with automated testing, security scanning, and compliance validation.
• Design observability platforms that provide comprehensive monitoring, logging, and alerting.
• Build self-service automation enabling digital teams to deploy infrastructure safely and rapidly.
• Establish GitOps practices and automated rollback mechanisms for pharmaceutical production systems.
• Design seamless integrations between on-premises pharmaceutical systems and cloud platforms.
• Build disaster recovery and business continuity solutions meeting pharmaceutical regulatory requirements.
• Optimize hybrid cloud costs through FinOps practices and automated resource management.
• Lead technical architecture discussions with Digital R&D, Manufacturing, and Corporate peer organizations.
• Provide consultative guidance on cloud, AI, and infrastructure strategies for critical pharmaceutical initiatives.
• Co-design enterprise solutions that balance innovation speed with GxP compliance requirements.
• Translate business challenges into technical solutions aligned with Sanofi’s AI transformation roadmap.
• Work closely with Enterprise Architecture on strategic technology initiatives and standards development.
• Provide solution-level architectural decisions in line with enterprise architectural standards.
• Contribute to architectural decision frameworks for cloud, AI, and infrastructure domains.
• Aligning foundational technology capabilities with digital innovation requirements across the organization.
• Define technical patterns, standards, and best practices for the emerging Solutions Engineering team.
• Establish solution design methodologies that balance pharmaceutical compliance with innovation speed.
• Participate in hiring and developing additional Solutions Engineers across specialized domains.
• Create technical documentation, reference architecture, and implementation guides.
• Design and promote AIOps capabilities for infrastructure and DevOps automation.
• Oversee implementation of intelligent monitoring, predictive analytics, and automated remediation.
• Collaborate with the agentic AI core team to integrate AI-powered operations into the pharmaceutical technology stack.
• Drive adoption of ML-powered capacity planning, anomaly detection, and self-healing systems.

Benefits

• high-quality healthcare
• prevention and wellness programs
• at least 14 weeks’ gender-neutral parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Senior