Technical Architect (Gen AI)

San R&D Business Solutions LLC • Santa Clara, CA

3d • Onsite

About The Position

This is a senior architecture role with direct ownership of how Generative AI and agentic capabilities are designed, integrated, governed, and scaled across the enterprise. The Technical Architect will define the overall AI platform strategy using Google Cloud Vertex AI, Agentspace, and related technologies, ensuring secure, reliable, and business-aligned adoption of AI solutions.

The role requires deep hands-on expertise in Gen AI, cloud architecture, and enterprise system integration. You will collaborate with engineering, product, and business stakeholders to establish standards for agent development, orchestration, observability, and lifecycle management while driving real-world implementations integrated with platforms such as SAP, Salesforce, and ServiceNow.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related discipline
• 14+ years of experience in AI/ML, cloud engineering, platform engineering, or enterprise architecture
• 3+ years hands-on experience with GCP Vertex AI including Agentspace, Agent Builder, Vector Search or Matching Engine, Search & Conversation, with ability to explain real implementations
• 2+ years building Generative AI applications such as AI assistants, retrieval-based systems, or LLM-powered workflows
• 5+ years strong Python development experience building production backend services, APIs, or microservices
• Practical integration experience with at least one enterprise platform – SAP, Salesforce, or ServiceNow
• 3+ years cloud deployment experience using GCP services such as Cloud Run, Cloud Functions, or Kubernetes
• 1–2 years experience operationalizing AI systems including monitoring, reliability, prompt or model management, and error handling
• Working knowledge of enterprise security, access control, and responsible handling of sensitive data
• Strong communication skills with ability to clearly articulate architecture decisions and past contributions

Nice To Haves

• Experience with multi-cloud AI environments such as Azure OpenAI, Copilot Studio, or OpenAI API
• Background in Agent Ops, LLMOps, and governance frameworks
• Experience designing enterprise-grade agentic systems at scale
• Knowledge of responsible AI practices, compliance, and model risk management
• Prior experience defining reference architectures and mentoring large engineering teams

Responsibilities

• Define and own the end-to-end architecture for GCP Vertex AI and Agentspace implementations
• Establish standards for agent development patterns, grounding strategies, memory management, and context engineering
• Design integration frameworks connecting AI agents with enterprise platforms including SAP, Salesforce, and ServiceNow
• Architect Agent-to-Agent coordination, orchestration, and on-behalf-of workflows
• Define approaches for testing, monitoring, observability, safety, and control in Gen AI systems
• Lead enterprise governance covering LLMOps, AgentOps, security, and lifecycle management
• Drive cloud-native deployment using GCP services such as Cloud Run, Cloud Functions, and Kubernetes
• Mentor technical teams and establish best practices for production-grade AI development
• Collaborate with stakeholders to shape AI roadmap and adoption strategy

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level