Staff AI Architect

As an AI Architect at Thermo Fisher Scientific, you will have the opportunity to design and deliver advanced AI/ML solutions that drive automation, optimization, and data-driven decision-making. Your role will involve defining architecture and roadmap for AI and intelligent applications across the organization, designing and implementing Retrieval-Augmented Generation (RAG) based AI solutions for enterprise use cases, and driving end-to-end AI/ML solution design from ideation to deployment and scaling. You will collaborate with business stakeholders, data scientists, and engineering teams to deliver impactful solutions and promote Agile/Scrum practices for effective and timely delivery. Key Responsibilities: - Define architecture and roadmap for AI and intelligent applications - Design and implement Retrieval-Augmented Generation (RAG) based AI solutions - Drive end-to-end AI/ML solution design and deployment - Identify opportunities for automation and AI adoption across business functions - Ensure scalability, reliability, and performance of AI and automation solutions - Collaborate with cross-functional teams to deliver impactful solutions - Translate business requirements into technical architecture and solution design - Drive innovation through adoption of emerging technologies including IoT and digital twins Qualifications Required: - Strong expertise in AI/ML and Generative AI with proven delivery at scale - Cloud-native architecture experience on AWS/Azure with Kubernetes (EKS/AKS) and CI/CD (GitHub Actions, Azure DevOps, Jenkins) - Solid data platform engineering background with experience in Databricks Lakehouse and scalable data processing/pipeline design - Hands-on experience across the Python ecosystem and ML frameworks with familiarity in experiment tracking and model registry - Deep experience with GenAI/LLM ecosystems, embeddings, vector databases, and RAG architectures end-to-end - Proficiency in prompt and workflow orchestration and integrating AI into enterprise architectures - Strong grasp of security, governance, and compliance with understanding of AI governance - Experience with observability, reliability engineering, and FinOps for data/AI platforms Thermo Fisher Scientific offers you the opportunity to lead enterprise-scale AI and automation transformation, work on cutting-edge intelligent applications and emerging technologies, and be part of a collaborative and innovation-driven environment with strong leadership and career growth opportunities. As an AI Architect at Thermo Fisher Scientific, you will have the opportunity to design and deliver advanced AI/ML solutions that drive automation, optimization, and data-driven decision-making. Your role will involve defining architecture and roadmap for AI and intelligent applications across the organization, designing and implementing Retrieval-Augmented Generation (RAG) based AI solutions for enterprise use cases, and driving end-to-end AI/ML solution design from ideation to deployment and scaling. You will collaborate with business stakeholders, data scientists, and engineering teams to deliver impactful solutions and promote Agile/Scrum practices for effective and timely delivery. Key Responsibilities: - Define architecture and roadmap for AI and intelligent applications - Design and implement Retrieval-Augmented Generation (RAG) based AI solutions - Drive end-to-end AI/ML solution design and deployment - Identify opportunities for automation and AI adoption across business functions - Ensure scalability, reliability, and performance of AI and automation solutions - Collaborate with cross-functional teams to deliver impactful solutions - Translate business requirements into technical architecture and solution design - Drive innovation through adoption of emerging technologies including IoT and digital twins Qualifications Required: - Strong expertise in AI/ML and Generative AI with proven delivery at scale - Cloud-native architecture experience on AWS/Azure with Kubernetes (EKS/AKS) and CI/CD (GitHub Actions, Azure DevOps, Jenkins) - Solid data platform engineering background with experience in Databricks Lakehouse and scalable data processing/pipeline design - Hands-on experience across the Python ecosystem and ML frameworks with familiarity in experiment tracking and model registry - Deep experience with GenAI/LLM ecosystems, embeddings, vector databases, and RAG architectures end-to-end - Proficiency in prompt and workflow orchestration and integrating AI into enterprise architectures - Strong grasp of security, governance, and compliance with understanding of AI governance - Experience with observability, reliability engineering, and FinOps for data/AI platforms Thermo Fisher Scientific offers you the opportunity to lead enterprise-scale AI and automation transformation, work on cutting-edge intelligent applications and emerging technologies, and be part of a collaborative and innovation-driven environment wi