Gen AI Architect

Santa Clara County, CA - USA

Monthly Salary: Not Disclosed

Posted on: 13 hours ago

Vacancies: 1 Vacancy

Job Summary

Job Title: Gen AI Architect

Location: Santa Clara CA

Duration: Contract

Need 14 years of experience resume.

Accepts only H1b Visa

As a Technical Architect specializing in LLMs and Agentic AI you will own the architecture strategy and delivery of enterprise-grade AI solutions. You will 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:

Primary Responsibilities:

Architect Scalable GenAI Solutions: Lead the design of enterprise architectures for LLM and multi-agent systems ensuring scalability resilience and security across Azure and GCP platforms.
Technology Strategy & Guidance: Provide strategic technical leadership to customers and internal teams aligning GenAI projects with business outcomes.
LLM & RAG Applications: Architect and guide development of LLM-powered applications assistants and RAG pipelines for structured and unstructured data.
Agentic AI Frameworks: Define and implement agentic AI architectures leveraging frameworks like Lang Graph AutoGen DSPy and cloud-native orchestration tools.
Integration & APIs: Oversee integration of OpenAI Azure OpenAI and GCP Vertex AI models into enterprise systems including MuleSoft Apigee connectors.
LLMOps & Governance: Establish LLMOps practices (CI/CD monitoring optimization cost control) and enforce responsible AI guardrails (bias detection prompt injection protection hallucination reduction).
Enterprise Governance: Lead architecture reviews governance boards and technical design authority for all LLM initiatives.
Collaboration: Partner with data scientists engineers and business teams to translate use cases into scalable secure solutions.
Documentation & Standards: Define and maintain best practices playbooks and technical documentation for enterprise adoption.
Monitoring & Observability: Guide implementation of Agen tops dashboards for usage adoption ingestion health and platform performance visibility.

Secondary Responsibilities:

Innovation & Research: Stay ahead of advancements in OpenAI Azure AI and GCP Vertex AI evaluating new features and approaches for enterprise adoption.
Proof of Concepts: Lead or sponsor PoCs to validate feasibility ROI and technical fit for new AI capabilities.
Ecosystem Expertise: Remain current on Azure AI services (Cognitive Search AI Studio Cognitive Services) and GCP AI stack (Vertex AI Big Query Matching Engine).
Business Alignment: Collaborate with product and business leadership to prioritize high-value AI initiatives with measurable outcomes.
Mentorship: Coach engineering teams on LLM solution design performance tuning and evaluation techniques.

Thanks & Regards