Technical Architect AI, GCP

Job Title : Technical Architect AI, GCP

Location : Santa Clara, CA 95054 (Onsite)

FTE Position

Job / Role Description :

As a Technical Architect specializing in LLMs and Agentic AI, you will own the architecture, strategy, and delivery of Enterprise-grade AI solutions. Work with cross-functional teams and customers to define the AI roadmap, design scalable solutions, and ensure responsible deployment of Generative AI across the organization.

Skills / Experience :

• Experience 10+ years of experience in AI / ML-related roles, with a strong focus on LLM's & Agentic AI technology
• Generative AI Solution Architecture (2-3 years) Proven experience in designing and architecting GenAI applications, including Retrieval-Augmented Generation (RAG), LLM orchestration (LangChain, LangGraph), and advanced prompt design strategies
• Backend & Integration Expertise (5+ years) Strong background in architecting Python-based Microservices, APIs, and orchestration layers that enable tool invocation, context management, and task decomposition across cloud-native environments (Azure Functions, GCP Cloud Functions, Kubernetes)
• Enterprise LLM Architecture (2-3 years) Hands-on experience in architecting end-to-end LLM solutions using Azure OpenAI, Azure AI Studio, Hugging Face models, and GCP Vertex AI, ensuring scalability, security, and performance
• RAG & Data Pipeline Design (2-3 years) Expertise in designing and optimizing RAG pipelines, including enterprise data ingestion, embedding generation, and vector search using Azure Cognitive Search, Pinecone, Weaviate, FAISS, or GCP Vertex AI Matching Engine
• LLM Optimization & Adaptation (2-3 years) Experience in implementing fine-tuning and parameter-efficient tuning approaches (LoRA, QLoRA, PEFT) and integrating memory modules (long-term, short-term, episodic) to enhance agent intelligence
• Multi-Agent Orchestration (2-3 years) Skilled in designing multi-agent frameworks and orchestration pipelines with LangChain, AutoGen, or DSPy, enabling goal-driven planning, task decomposition, and tool / API invocation
• Performance Engineering (2-3 years) Experience in optimizing GCP Vertex AI models for latency, throughput, and scalability in enterprise-grade deployments
• AI Application Integration (2-3 years) Proven ability to integrate OpenAI and third-party models into enterprise applications via APIs and custom connectors (MuleSoft, Apigee, Azure APIM)
• Governance & Guardrails (1-2 years) Hands-on experience in implementing security, compliance, and governance frameworks for LLM-based applications, including content moderation, data protection, and responsible AI guardrails
• Provide constructive feedback during code reviews and be open to receiving feedback on your own code
• Bachelor's or Master's degree in Computer Science, Data Science, or a related field; Prior experience in working on Agile / Scrum projects with exposure to tools like Jira / Azure DevOps
• Secondary Skills Knowledge of MCP's and A2A SDK; Version Control : Proficiency with Version Control tools like Git; Agile Methodologies - Experience working in Agile development environments

Primary Responsibilities :

Secondary Responsibilities :