OCI AIDP Platform Architect

OCI AIDP Platform Architect
Remote (US)
Full-Time Opportunity / FTE Only 

Job Overview:

Lead the architecture and design of a governed, scalable, AI-ready OCI AIDP Lakehouse platform that enables trusted enterprise data products, advanced analytics, GenAI, and acquisition-ready data integration. 

Job Description:

• We are seeking an experienced OCI AIDP Platform Architect to lead the architecture, design, and enablement of the Enterprise Data Lakehouse on Oracle Cloud Infrastructure and Oracle AI Data Platform. This role will define the target-state platform architecture across cloud foundation, data ingestion, storage, processing, governance, security, observability, semantic enablement, and AI-ready consumption patterns. The architect will partner closely with data engineering, DevOps, security, governance, business, and leadership stakeholders to translate business priorities into durable, scalable, secure, and implementable platform capabilities.
• This role reports to the Principal Data Engineering Lead and operates within the Data Governance, AI & Analytics organization as part of the Enterprise Data Lakehouse Architecture and Platform team. The ideal candidate brings deep hands-on experience with cloud data platforms, OCI architecture, lakehouse services, enterprise-scale data modernization, regulated data environments, and AI-ready architecture patterns. This individual will serve as a trusted technical leader who can guide discovery, shape architectural standards, validate design decisions, and enable teams to deliver production-ready data and AI platform capabilities.

What You Will Do:
Platform Architecture:

• Define the end-to-end OCI AIDP Lakehouse architecture across ingestion, storage, processing, metadata, governance, semantic enablement, serving, AI consumption, observability, and operations.
• Design scalable OCI landing zone patterns, including compartments, networking, tenancy structure, environment strategy, secrets management, encryption, key management, monitoring, logging, and security guardrails.
• Establish reusable architecture standards for onboarding enterprise domains such as Provider, Product, Claims, Member, Finance, and future acquisition data sources.
• Create durable platform blueprints for domain onboarding, source integration, data product publication, metadata capture, governed consumption, and production operations.

OCI / AIDP Service Strategy

• Map business, engineering, governance, and AI platform requirements to appropriate OCI and Oracle AIDP capabilities, including OCI Data Integration, GoldenGate, Data Flow, Object Storage, Autonomous AI Lakehouse, Autonomous Data Warehouse, OCI Data Catalog, Data Safe, OCI DevOps, Logging, Monitoring, and OCI Generative AI.
• Lead service selection and design decisions by validating enterprise standards, existing Oracle footprint, licensing and entitlements, integration constraints, performance needs, security requirements, and operating model considerations.
• Partner with DevOps, infrastructure, and security teams to ensure the platform is reproducible, automated, observable, resilient, secure, compliant, and ready for production-scale adoption.

AI-Ready and Governed Architecture

• Define AI-ready architecture patterns for GenAI, RAG, embeddings, vector search, semantic models, knowledge graphs, agent memory, natural-language analytics, and agentic business workflows.
• Ensure AI and analytics consumption patterns inherit approved access controls, lineage, metadata, certified business definitions, quality signals, data classifications, and governance constraints.
• Establish responsible AI platform guardrails so AI-enabled workloads remain secure, auditable, explainable, human-owned, and appropriate for healthcare and regulated data environments.

Architecture Governance

• Lead architecture reviews, technical discovery sessions, solution walkthroughs, and design validation discussions with engineering, platform, governance, security, business, and executive stakeholders.
• Produce and maintain professional architecture artifacts, including reference architectures, solution blueprints, architecture decision records, service maps, design standards, guardrails, and deployment patterns.
• Identify architectural risks, assumptions, dependencies, trade-offs, and mitigation options across pilot delivery, enterprise scale-out, acquisition onboarding, and long-term platform operations.

What You Will Deliver

• Target-state OCI AIDP Lakehouse reference architecture covering platform foundation, data services, governance integration, security, observability, AI enablement, and operating model considerations.
• OCI landing zone, service-mapping, environment strategy, and deployment blueprint for pilot implementation and enterprise scale-out.
• Domain onboarding architecture pattern for priority enterprise domains, including source integration, data product publication, metadata capture, access control, and consumption readiness.
• AI-ready architecture patterns for semantic enablement, RAG, embeddings, vector search, GenAI, agentic workflows, and governed AI consumption.
• Security, privacy, governance, lineage, metadata, data quality, observability, resiliency, and cost-management guardrails for the OCI AIDP Lakehouse platform.
• Architecture decision records, reusable design standards, review materials, dependency maps, implementation guidance, and executive-ready architecture summaries.

Required Qualifications, Capabilities, and Skills

• 12+ years of experience in enterprise architecture, cloud architecture, data platform architecture, data engineering architecture, or related senior technology leadership roles.
• 5+ years of experience designing cloud-native data platforms, lakehouse architectures, enterprise data modernization programs, or large-scale analytics platforms.
• Hands-on architecture experience with Oracle Cloud Infrastructure and strong understanding of OCI-native platform, data, security, networking, monitoring, and DevOps capabilities.
• Deep understanding of lakehouse architecture, medallion patterns, data products, metadata management, lineage, data quality, governance, semantic enablement, and secure consumption patterns.
• Experience designing secure, resilient, scalable, and compliant platforms for regulated data environments, preferably healthcare payer, claims, member, provider, finance, PHI, HIPAA-adjacent, or privacy-sensitive domains.
• Ability to lead architecture discussions, communicate trade-offs, influence decisions, and present complex technical recommendations to executive, business, governance, security, platform, and engineering audiences.

Preferred Qualifications, Capabilities, and Skills

• Experience architecting enterprise-scale data lakehouse or AI data platform capabilities using Oracle AIDP, Autonomous AI Lakehouse, Autonomous Data Warehouse, OCI Data Integration, GoldenGate, Object Storage, OCI Data Catalog, OCI DevOps, Data Safe, Cloud Guard, Logging, Monitoring, or comparable cloud-native services.
• Demonstrated experience with modern lakehouse and open data technologies such as Apache Iceberg, Delta Lake, Parquet, ORC, Spark, distributed processing frameworks, streaming integration, vector databases, feature stores, or comparable enterprise data ecosystem capabilities.
• Experience enabling AI-ready data foundations for GenAI, RAG, embeddings, vector search, semantic models, knowledge graphs, model deployment, MLOps, prompt orchestration, and agentic workflow enablement.
• Background designing platforms for healthcare payer, provider, claims, member, product, finance, acquisition integration, PHI protection, privacy, security, and other regulated or sensitive data environments.
• Experience leading technical discovery, architecture reviews, proof-of-concept validation, platform adoption planning, implementation roadmaps, and executive-level solution discussions.
• Experience producing professional architecture artifacts such as reference architectures, solution blueprints, architecture decision records, governance playbooks, technical standards, service maps, and platform enablement materials.
• Familiarity with enterprise architecture frameworks, DataOps, DevOps, FinOps, observability, SRE practices, infrastructure as code, automated deployment, production support models, and cloud cost optimization.
• Relevant Oracle, cloud architecture, data engineering, security, governance, enterprise architecture, or AI/ML certifications are preferred.