Gen AI Architect

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

Akhil

Key Skills

APIs,Pegasystems,Spring,SOAP,.NET,Hybris,Solution Architecture,Service-Oriented Architecture,Adobe Experience Manager,J2EE,Java,Oracle

Employment Type : Full Time

Experience : years

Vacancy : 1