Enterprise Cloud Data & AI Architect / AI Product Leader

Job Title: Enterprise Cloud Data & AI Architect / AI Product Leader

Location: San Jose CA

Duration: Long Term Contract

(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