Staff AI Architect

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.\nDescription\nWe are seeking an experienced AI Architect to design and deliver advanced AI/ML solutions that drive automation, optimization, and data-driven decision-making. This role will focus on building scalable AI architectures, leading end-to-end AI/ML initiatives, and enabling enterprise-wide adoption of intelligent solutions.\nExperience Required\n10+ years of overall professional experience\n5+ years of experience as an AI Architect or similar role\nProven experience in designing and implementing at least 3-4 AI/ML initiatives end-to-end\nKey Responsibilities\nDefine architecture and roadmap for AI and intelligent applications across the organization\nDesign and implement Retrieval-Augmented Generation (RAG) based AI solutions for enterprise use cases\nDesign and implement scalable, robust, and reusable AI/ML solutions\nDrive end-to-end AI/ML solution design from ideation to deployment and scaling\nIdentify opportunities for automation and AI adoption across business functions\nEnsure scalability, reliability, and performance of AI and automation solutions\nCollaborate with business stakeholders, data scientists, and engineering teams to deliver impactful solutions\nTranslate business requirements into technical architecture and solution design\nPromote Agile/Scrum practices for effective and timely delivery\nDrive innovation through adoption of emerging technologies including IoT and digital twins\nRequired Skills & Qualifications\nStrong 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)\nCloud-native architecture experience on AWS/Azure with Kubernetes (EKS/AKS) and CI/CD (GitHub Actions, Azure DevOps, Jenkins)\nSolid data platform engineering background: Databricks Lakehouse and/or cloud storage (S3 or equivalent), and scalable data processing/pipeline design\nHands-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\nDeep experience with GenAI/LLM ecosystems: providers (Azure OpenAI/OpenAI, Anthropic Claude, AWS Bedrock), orchestration (LangChain, LlamaIndex, Semantic Kernel), and agent frameworks (LangGraph, CrewAI, AutoGen)\nPractical expertise in RAG architectures end-to-end: ingestion pipelines, chunking/metadata enrichment, embeddings, vector retrieval, reranking, grounding/citation\nExperience with embeddings (OpenAI, Cohere, Bedrock Titan, sentence-transformers) and vector databases (Pinecone, Weaviate, Milvus, pgvector, OpenSearch vector engine)\nProficiency in prompt and workflow orchestration (prompt templates, guardrails, tool/function calling) and integrating AI into enterprise architectures\nStrong 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\nUnderstanding of AI governance (model risk, prompt/output filtering, human-in-the-loop, audit logging, data lineage, responsible AI)\nExperience with observability, reliability engineering, and FinOps for data/AI platforms\nPreferred Qualifications\nExperience with microservices frameworks such as FastAPI\nFamiliarity with API patterns such as REST and GraphQL\nExperience or understanding of UI/UX design principles and collaboration with design teams\nExposure to IoT and digital twin technologies\nCertifications in AI/ML, cloud (AWS/Azure), or data engineering\nKnowledge of GxP processes and regulated environments\nKey Competencies\nStrong architectural thinking and solution design\nInnovation and continuous improvement mindset\nStrong problem-solving and decision-making skills\nAbility to manage complex, cross-functional programs\nEducation\nBachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field\nWhy Join Us\nOpportunity to lead enterprise-scale AI and automation transformation\nWork on cutting-edge intelligent applications and emerging technologies\nCollaborative and innovation-driven environment\nStrong leadership and career growth opportunities\n\n]]>