Work Schedule
Standard (Mon-Fri)
Environmental Conditions
Office
Job Description
As 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.
Description
We 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 Required
- 15+ years of overall professional experience
- 5+ years of experience in AI/ML implementations
- 5+ years of hands-on experience in automation initiatives
- 5+ years of experience in managing AI/ML and automation engineering teams.
Key Responsibilities
- Lead, mentor, and scale high-performing teams including AI/ML engineers, data scientists, and automation specialists, with responsibility for hiring, coaching, and performance management
- Establish strong leadership practices, fostering collaboration, innovation, and accountability across teams
- Drive cross-functional alignment with business, technology, and executive stakeholders
- Lead and manage AI/ML and automation teams to deliver high-impact solutions
- Define strategy and roadmap for AI and intelligent applications across the organization
- Drive end-to-end AI/ML project delivery from ideation to deployment and scaling
- Identify opportunities for automation and AI adoption across business functions
- Mentor and guide teams to ensure successful delivery of AI/ML initiatives
- Ensure scalability, reliability, and performance of AI and automation solutions
- Collaborate with business stakeholders, data scientists, and engineering teams
- Promote Agile/Scrum practices for effective and timely delivery
- Drive innovation through adoption of emerging technologies including IoT and digital twins
Required Skills & Qualifications
- Strong 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 design
- Hands-on experience across the Python ecosystem (Python, Pandas, NumPy) and ML frameworks (Scikit-learn, XGBoost, PyTorch, TensorFlow) with familiarity in experiment tracking and model registry
- Deep 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/citation
- Experience 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 architectures
- Strong 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 standards
- Understanding 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 platforms
Preferred Qualifications
- Experience with microservices frameworks such as FastAPI
- Familiarity with API patterns such as REST and GraphQL
- Experience or understanding of UI/UX design principles and collaboration with design teams
- Exposure to IoT and digital twin technologies
- Certifications in AI/ML, cloud (AWS/Azure), or data engineering
- Knowledge of GxP processes and regulated environments
Key Competencies
- Strategic thinking and execution
- Leadership and team development
- Innovation and continuous improvement mindset
- Strong problem-solving and decision-making skills
- Ability to manage complex, cross-functional programs
Education
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field
Why Join Us
- Opportunity to lead enterprise-scale AI and automation transformation
- Work on cutting-edge intelligent applications and emerging technologies
- Collaborative and innovation-driven environment
- Strong leadership and career growth opportunities
