Job Description
The role requires a deep understanding of AI services, industry hyperscalers including infrastructure, data management, and distributed applications, as well as a proficiency in tools used to manage services in cloud environments. The ideal candidate will be comfortable architecting and deploying cloud-native and hybrid applications using native services and components on major hyperscaler platforms.
Mission
This person will play a crucial role in developing service innovation, optimizing processes, and delivering insights that empower the organization to make informed, data-driven decisions. They are passionate about cloud enterprise architecture and is collaborative and driven to apply their technical skills to real-world applications. This role will contribute to portfolio management and business development of Oracle Customer Success Services offerings for our customers that feature the latest Oracle technologies and capabilities. The architect will ensure that all deployments adhere to security, compliance, and cost optimization best practices for each hyperscaler.
Qualifications
Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, Engineering or related field required; Ph.D. preferred
Multiple cloud certifications such as Oracle Certifications: OCI Associate Architect, OCI Architect Professional; AWS Certifications: AWS Solutions Architect, AWS Security Specialist, Microsoft Certifications: Azure Security Engineer, Associate, Azure Solutions Architect, Google Certifications: GCP Cloud Architect Certification
Certification as TOGAF and/or Zachman Enterprise Architect preferred
Experience
15+ years in IT services, including significant direct experience in customer facing and service management
Proficient with cloud platforms (OCI, GCP, Azure, AWS) and environments on-Premise for Enterprise application operations
Hands-on experience architecting, deploying, and managing enterprise workloads and data migrations on at least two major hyperscaler platforms (AWS, Azure, GCP).
Familiarity with natural language processing (NLP), computer vision, and deep learning
Prior experience deploying and maintaining AI models in production environments
Commercial constructs and contract management, including construction of TCO analyses and pricing for complex service offers
Large scale IT project and program management, including major transformation, migration, and solution deployment projects
Strong analytical and problem-solving abilities to translate business problems into technical requirements
Excellent written and verbal communication capability to convey complex concepts to both technical and non-technical audiences
Skills
Automation Tools: Deep expertise with infrastructure-as-code and automation for hyperscalers (CloudFormation for AWS, ARM/Bicep for Azure, Deployment Manager for GCP, and cloud-agnostic tools like Ansible or Terraform)
Monitoring: Familiarity with hyperscaler-native monitoring/logging tools: OCI OEM and O&M, AWS CloudWatch, Azure Monitor, GCP Operations Suite and cloud agnostic tools like Prometheus, Grafana or Kibana
Networking Elements: subnets, route tables, gateways, DNS, load balancers, firewalls, VPNs
Cloud Networking: VPCs, VCNs, WAN connectivity, Fastconnect (OCI), ExpressRoute (Azure), Direct Connect (AWS), Cloud Interconnect (GCP)
Hybrid Security: OCI Vault (Oracle), Key Vault (Azure), KMS (AWS/GCP), and cross-cloud identity (OCI IAM, Azure AD, AWS IAM, Google Workspaces)
Resilience: Ability to analyze and optimize cloud resource allocation, selection of instance types, and storage tiers to balance performance, HA, Business Continuity, and cost in hyperscaler environments
Structured Data : Oracle Database, NoSQL, MySQL, and other databases
Data Processing : Thorough grasp of Spark, Kafka, Hadoop, MapReduce
Data Design : Proficient in handling large datasets, data structures and algorithms for machine learning workflows
Analytics : Comprehensive predictive, diagnostic and prescriptive analytics skills and usage of relevant tools
Development Tools : Language fluency in Python, R, SQL, Java, Langchain
AI/ML Frameworks : TensorFlow, PyTorch, and GenAI Frameworks like Autogen
Data Science : MLOps practices requiring projects, model deployments, data science SDKs, Jupyterlab notebooks
AI Governance : Understanding of ethical AI and responsible AI practices
DevOps : tooling such as Jenkins, Gitlab, and testing tools such as Selenium, Loadrunner and RUEI
#LI-VC7
Responsibilities
Key Responsibilities
As a technical individual contributor, this role will provide leadership across the CSS organization and throughout Oracle by demonstrating domain expertise in:
Solution Development: Design, develop, and implement data layer architectures, Oracle applications, and AI systems to solve specific business problems and improve workflows. Architect scalable, secure, and automated solutions targeting multicloud and hybrid-cloud environments, ensuring interoperability among Oracle Cloud, AWS, Azure, and GCP ecosystems.
Service Design: Build repeatable offerings for global customers with mission-critical estates in multicloud enterprise environments. Incubate services from Oracle and partners in prototypes, demos, and package for delivery-ready implementations. Leverage native services (e.g., AWS Lambda, Azure Functions, GCP Cloud Run) and infrastructure-as-code for automated, cloud-agnostic deployments.
Deployment and Automation: Lead the end-to-end deployment of modern applications and workloads using CI/CD and DevOps methodologies, utilizing industry-standard tools and native pipelines available in AWS (CodePipeline), Azure DevOps, and GCP Cloud Build.
Cloud Governance & Security: Ensure robust multi-cloud security by implementing Identity and Access Management, network segmentation, encryption, key management, and compliance mapping specific to each hyperscaler. Conduct regular assessments for adherence to regulatory standards (GDPR, HIPAA, PCI, SOC 2, etc.).
Cost Management and Optimization: Design and implement cost-effective architecture, recommending and applying tools and best practices for budgeting, monitoring, and optimizing cloud spend across hyperscalers.
Data Processing: Collect, preprocess, and analyze large datasets to support data pipelines. This may include data cleaning, transformation, and augmentation. Leverage (and integrate between) managed data services such as AWS RDS, Azure SQL Database, GCP BigQuery, and cloud-native storage, ensuring high availability and disaster recovery.
Collaboration: Work closely with cross-functional teams, including architects, developers, software engineers, and business stakeholders, to define project goals and deliver AI solutions that meet organizational needs.] Liaise with hyperscaler customer engineering and support organizations as appropriate.
Documentation and Reporting: Document model design, methodologies, and results. Report findings and progress to technical and non-technical stakeholders. Exercise comportment with extremely strong customer-facing presentation and interaction skills at executive management and C-Level. Develop and maintain architecture blueprints, sales guides, and presales best practices for multicloud operations.
Deployment and Maintenance: Deploy services in prototypes, pilots, and production environments and continuously monitor with native monitoring and logging tools like OCI Cloud Guard, AWS CloudWatch, Azure Monitor, and GCP Operations Suite for proactive incident detection and response.
Disclaimer:
**Certain US customer or client-facing roles may be required to comply with applicable requirements, such as immunization and
