Role: Cloud Architect with expertise in Generative AI --Senior GenAi/ Agentic Lead [Need Local]

Location: Santa Clara Location - Onsite Day one

Locals are preferred

We are seeking a highly skilled Cloud Architect with expertise in Generative AI, Copilot Studio, and multi-cloud platforms spanning Azure (including Azure AI Foundry), AWS, and Google Cloud. This role will design scalable, secure, and production-ready AI systems, enabling RAG, agentic workflows, and enterprise copilots.

Core Responsibilities:

• Architect end-to-end Generative AI solutions, including model serving (vLLM, TGI), API integration, and user interaction layers.
• Design and implement RAG architecture using vector stores, embeddings, hybrid search, and re-ranking to embed enterprise knowledge into LLMs.
• Create agentic systems, enabling multi-agent collaboration for complex, stateful workflows and reasoning-driven automation.
• Develop and govern Copilots in Copilot Studio, including connectors, actions, plugins, DLP rules, environment strategy, and integration with Microsoft 365 and enterprise systems.
• Leverage Azure AI Foundry (prompt flow, evaluators, safety, model orchestration) to operationalize LLM applications at scale.
• Evaluate and optimize AI system performance, balancing quality, latency, throughput, cost efficiency, and safety compliance.
• Implement Responsible AI, security, and HITL (HumanintheLoop) controls, ensuring compliance in regulated environments.-in-the-Loop) controls, ensuring compliance in regulated environments.
• Produce clear, maintainable documentation for architecture, patterns, and operational processes.

Required Qualifications

• 8–10 years of experience in cloud architecture or enterprise software engineering.
• 3+ years of hands-on experience designing or delivering Generative AI or LLM applications.
• Proven experience with Azure AI Foundry, Azure OpenAI, and Copilot Studio (actions, connectors, governance, M365 integration).
• Experience deploying AI solutions on AWS (Bedrock, SageMaker) and/or GCP (Vertex AI).
• Hands-on experience with RAG, vector databases (Azure AI Search, Pinecone, OpenSearch, Vertex Matching Engine), embeddings, and hybrid search.
• Deep understanding of cloud security (IAM/RBAC, Key Vault/KMS, VPC/PrivateLink, token safety).
• Experience with Kubernetes (AKS/EKS/GKE), containerization, API frameworks (FastAPI, Node.js, .NET), Python, TypeScript, or C#/.NET.
• Working knowledge of transformer architectures and model adaptation techniques (fine-tuning, LoRA, prompt engineering).
• Familiarity with AI Ops / MLOps tools such as Prompt Flow, MLflow, SageMaker Pipelines, or Vertex Pipelines.

Preferred Qualifications

• Experience implementing agent-based systems using frameworks like LangChain, LlamaIndex, Semantic Kernel, or AutoGen.
• Background working with enterprise data ecosystems (Databricks, Snowflake, BigQuery, Redshift).
• Knowledge of Responsible AI frameworks, guardrails, safety filters, PII redaction, and evaluation methodologies.
• Experience in regulated industries (healthcare, finance, government), with understanding of compliance controls.
• Experience with observability (OpenTelemetry, Prometheus/Grafana, App Insights) for AI workloads.

Education:

Bachelor’s/ Masters in Computer Science, Engineering, Information Systems, Data Science, or related field (required).