Job Title: Enterprise Cloud Data & AI Architect / AI Product Leader
Location: San Jose CA
Duration: Long Term Contract
Client: Sephora
(Alternate titles depending on organization: Principal Data & AI Architect, Head of Enterprise AI Platforms, Director Cloud Data & AI, Lead AI Solutions Architect)
Job Summary
We are seeking a highly accomplished Enterprise Cloud Data & AI Architect with deep expertise in cloud-native data platforms, advanced AI/ML, Generative AI, and Agentic AI systems, coupled with strong product leadership and strategic advisory capabilities.
This role is responsible for architecting, governing, and delivering enterprise-scale Data & AI ecosystems across multi-cloud environments (AWS, Azure, Google Cloud Platform), enabling data-driven decision intelligence, AI-powered automation, and next-generation digital products.
The ideal candidate brings 18+ years of experience leading large-scale transformations across industries, translating business vision into scalable, secure, and compliant Data, Analytics, and AI solutions, while influencing senior stakeholders and mentoring high-performing technical teams.
Key Responsibilities
Enterprise Data & AI Architecture
Define and lead enterprise-wide Data & AI architecture strategies, including Lakehouse, Data Mesh, and Data Fabric patterns.
Architect scalable, secure, and interoperable cloud-native data platforms on AWS, Azure, Google Cloud Platform, Snowflake, Databricks, and Palantir.
Design reusable data products, APIs, and domain-driven architectures that eliminate tight coupling and enable cross-team scalability.
Establish architectural standards, reference architectures, and blueprints aligned with TOGAF and enterprise governance models.
Generative AI, Agentic AI & Advanced AI Solutions
Design, develop, and deploy Generative AI and Agentic AI solutions, including multi-agent systems, RAG pipelines, and autonomous workflows.
Lead adoption of platforms such as OpenAI, Anthropic Claude, Google Gemini, AWS Bedrock, Snowflake Cortex, Databricks Mosaic AI, Vertex AI.
Architect intelligent agents using LangChain, LangGraph, CrewAI, AutoGPT, Semantic Kernel, LlamaIndex, MCP, A2A, and related orchestration frameworks.
Optimize LLM inference, embeddings, vector databases (Pinecone, Milvus, Chroma), and cost-performance tradeoffs at enterprise scale.
AI/ML Engineering, MLOps & LLMOps
Lead design and governance of end-to-end ML, MLOps, AIOps, and LLMOps pipelines, ensuring reliability, observability, and scalability.
Implement model lifecycle management, monitoring, drift detection, explainability, and feedback loops using MLflow, Datadog, LangSmith, Arize, Azure AI Safety.
Oversee fine-tuning strategies (LoRA, QLoRA) and deployment of transformer-based models (GPT, BERT, LLaMA, Gemini, Mistral, etc.).
Data Engineering, Analytics & BI
Architect and optimize batch and streaming data pipelines using Spark, PySpark, Kafka, Kinesis, BigQuery, Redshift, Synapse, Delta Lake, Iceberg.
Lead large-scale ETL/ELT modernization across Informatica, SnapLogic, Fivetran, ADF, Airflow, and cloud-native services.
Enable advanced analytics and BI using Power BI, Tableau, Cognos, OBIEE, and modern semantic layers.
Product Strategy & Business Leadership
Define and govern Data & AI product vision, roadmaps, and KPIs, ensuring alignment with enterprise strategy and measurable ROI.
Partner with executive stakeholders to identify and prioritize high-value AI use cases across supply chain, healthcare, retail, finance, and life sciences.
Translate complex AI/ML concepts into actionable business outcomes for non-technical leaders.
Act as a strategic advisor and trusted partner across business, engineering, security, and compliance teams.
Governance, Security & Compliance
Design AI solutions compliant with HIPAA, GDPR, NIST, SOC2, and emerging Responsible AI frameworks.
Establish data governance, access controls, lineage, and cataloging using Collibra, Azure Purview, Google Cloud Platform Dataplex, and Informatica.
Ensure ethical AI adoption, model transparency, data privacy, and enterprise risk management.
Leadership & Collaboration
Lead and mentor cross-functional teams of architects, data engineers, data scientists, and AI engineers.
Drive consensus in highly matrixed environments without direct authority.
Support presales, PoCs, RFPs, and executive-level architecture reviews.
Required Qualifications
18+ years of experience in Data Architecture, Analytics, AI/ML, and Cloud Platforms
Proven experience as an Enterprise or Principal Architect delivering large-scale, mission-critical solutions
Deep hands-on expertise with AWS, Azure, Google Cloud Platform, Databricks, Snowflake
Strong programming skills in Python, SQL, PySpark (Scala/Java a plus)
Extensive experience with Generative AI, LLMs, Agentic AI, RAG, and AI orchestration frameworks
Solid background in Data Engineering, BI/DWH, and Advanced Analytics
Strong stakeholder management, communication, and leadership skills
Certifications (Preferred / Required)
TOGAF Certified
AWS Certified Solutions Architect
Azure Solutions Architect Expert
Google Cloud Platform Professional Cloud Architect
Databricks Certified Professional
SnowPro Advanced Architect
SAFe / PMP / PGMP (preferred)
Education
PhD (or PhD-level research) in Computer Science, Artificial Intelligence, or Data Science (preferred)
Master s degree in Computer Applications, Computer Science, or related field
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