Responsibilities
Lead endtoend AI solution architecture from concept to production
Develop and deploy Pythonbased AI/ML and GenAI solutions using PyTorch, TensorFlow, Scikitlearn, and GenAI frameworks
Design and implement GenAI solutions on Google Cloud Platform using Gemini (RAG, embeddings, agents, prompt engineering)
Build Python APIs and services for AI inference and orchestration
Integrate AI capabilities with Oracle (Fusion, ERP) and Salesforce (Sales/Service/Data Cloud, APIs)
Define scalable architectures covering data ingestion, model inference, security, and observability
Ensure Responsible AI practices including governance, privacy, explainability, and access control
Support POCs, pilots, and production deployments, including performance and cost optimization
Collaborate in Agile teams using JIRA and Confluence and provide technical leadership as needed
Skills
Strong, handson Python expertise building productiongrade AI systems
Proven experience in architecting AI solutions on Google Cloud Platform
Handson experience with Gemini models and GenAI workflows (RAG, agents, embeddings)
Strong integration experience with Oracle and Salesforce platforms
Ability to work independently and make architectural decisions in ambiguous environments
Tools/Software
Python (advanced)
AI/ML frameworks: PyTorch, TensorFlow, Scikitlearn, GenAI tooling
Google Cloud Platform: Vertex AI, BigQuery, Cloud Functions/Run, IAM, monitoring
GenAI patterns: RAG, vector stores, orchestration, grounding
JIRA, Confluence
Experience
8+ years overall experience with 3 5+ years in AI/ML or GenAI architecture
Certification
None specified
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