AI & Intelligent Applications – Senior Manager

Work ScheduleStandard (Mon-Fri)Environmental ConditionsOfficeJob DescriptionAs part of the Thermo Fisher Scientific team, you’ll discover meaningful work that makes a positive impact on a global scale. Join our colleagues in bringing our Mission to life every single day to enable our customers to make the world healthier, cleaner and safer. We provide our global teams with the resources needed to achieve individual career goals while helping to take science a step beyond by developing solutions for some of the world’s toughest challenges, like protecting the environment, making sure our food is safe or helping find cures for cancer.DescriptionWe are seeking a highly experienced Senior Manager to lead AI and Intelligent Applications initiatives, driving enterprise-wide automation and advanced analytics programs. This role will focus on building, scaling, and managing AI/ML and automation capabilities, while delivering measurable business value through intelligent solutions.Experience Required15+ years of overall professional experience5+ years of experience in AI/ML implementations5+ years of hands-on experience in automation initiatives5+ years of experience in managing AI/ML and automation engineering teams.Key ResponsibilitiesLead, mentor, and scale high-performing teams including AI/ML engineers, data scientists, and automation specialists, with responsibility for hiring, coaching, and performance managementEstablish strong leadership practices, fostering collaboration, innovation, and accountability across teamsDrive cross-functional alignment with business, technology, and executive stakeholdersLead and manage AI/ML and automation teams to deliver high-impact solutionsDefine strategy and roadmap for AI and intelligent applications across the organizationDrive end-to-end AI/ML project delivery from ideation to deployment and scalingIdentify opportunities for automation and AI adoption across business functionsMentor and guide teams to ensure successful delivery of AI/ML initiativesEnsure scalability, reliability, and performance of AI and automation solutionsCollaborate with business stakeholders, data scientists, and engineering teamsPromote Agile/Scrum practices for effective and timely deliveryDrive innovation through adoption of emerging technologies including IoT and digital twinsRequired Skills & QualificationsStrong expertise in AI/ML and Generative AI with proven delivery at scale; ability to translate business problems into production-grade solutions and measurable outcomes (value, ROI)Cloud-native architecture experience on AWS/Azure with Kubernetes (EKS/AKS) and CI/CD (GitHub Actions, Azure DevOps, Jenkins)Solid data platform engineering background: Databricks Lakehouse and/or Snowflake, cloud storage (S3 or equivalent), and scalable data processing/pipeline designHands-on experience across the Python ecosystem (Python, Pandas, NumPy) and ML frameworks (Scikit-learn, XGBoost, PyTorch, TensorFlow) with familiarity in experiment tracking and model registryDeep experience with GenAI/LLM ecosystems: providers (Azure OpenAI/OpenAI, Anthropic Claude, AWS Bedrock), orchestration (LangChain, LlamaIndex, Semantic Kernel), and agent frameworks (LangGraph, CrewAI, AutoGen)Practical expertise in RAG architectures end-to-end: ingestion pipelines, chunking/metadata enrichment, embeddings, vector retrieval, reranking, grounding/citationExperience with embeddings (OpenAI, Cohere, Bedrock Titan, sentence-transformers) and vector databases (Pinecone, Weaviate, Milvus, pgvector, OpenSearch vector engine)Proficiency in prompt and workflow orchestration (prompt templates, guardrails, tool/function calling) and integrating AI into enterprise architecturesStrong grasp of security, governance, and compliance: IAM (Azure AD/Entra ID, AWS IAM, RBAC/ABAC), secrets management (KMS, Key Vault, HashiCorp Vault), and data privacy/regulatory standardsUnderstanding of AI governance (model risk, prompt/output filtering, human-in-the-loop, audit logging, data lineage, responsible AI)Experience with observability, reliability engineering, and FinOps for data/AI platformsPreferred QualificationsExperience with microservices frameworks such as FastAPIFamiliarity with API patterns such as REST and GraphQLExperience or understanding of UI/UX design principles and collaboration with design teamsExposure to IoT and digital twin technologiesCertifications in AI/ML, cloud (AWS/Azure), or data engineeringKnowledge of GxP processes and regulated environmentsKey CompetenciesStrategic thinking and executionLeadership and team developmentInnovation and continuous improvement mindsetStrong problem-solving and decision-making skillsAbility to manage complex, cross-functional programsEducationBachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related fieldWhy Join UsOpportunity to lead enterprise-scale AI and automation transformationWork on cutting-edge intelligent applications and emerging technologiesCollaborative and innovation-driven environmentStrong leadership and career growth opportunities