GenAI Architect: LLM, RAG & Agentic AI Solutions

SRS Consulting Inc; San Jose (CA); Hybrid; USD 180,000 - 240,000; Part time

Job summary

SRS Consulting Inc. in San Jose is seeking an experienced AI Technical Architect to architect GenAI, LLM, RAG, and Agentic AI solutions with a hands-on background in Python and enterprise AI delivery.

The role involves solutioning, architecture, and development of complex AI platforms across business domains. The ideal candidate has 8+ years of software/AI/ML/architecture experience, strong knowledge of LLM orchestration frameworks, vector databases, and cloud platforms (AWS/Azure/GCP).

Qualifications

• 8+ years of software/AI/ML/architecture experience.
• Hands-on with LLMs, GenAI, RAG, and Agentic AI.
• Machine Learning and NLP experience.
• Experience with LLM orchestration frameworks (LangChain, LangGraph, Semantic Kernel, etc.).
• Experience with vector databases and embeddings.
• Strong solution architecture and technical leadership.
• Experience with AWS, Azure, or GCP.
• Excellent communication and stakeholder management.

Responsibilities

• Design and architect enterprise GenAI, LLM, RAG, and Agentic AI solutions.
• Lead technical solutioning, POCs, and implementation roadmaps.
• Build and integrate LLM/RAG applications using Python.
• Design AI agents, tool calling, orchestration, and multi-step workflows.
• Integrate AI solutions with enterprise applications, databases, APIs, and cloud platforms.
• Provide hands-on technical leadership and guide development teams.

Skills

LLMs

GenAI

RAG

Agentic AI

ML

NLP

Python

Solution Architecture

Solutioning

Cloud

AWS

Azure

GCP

Job description

SRS Consulting Inc. in San Jose is seeking an experienced AI Technical Architect to architect GenAI, LLM, RAG, and Agentic AI solutions with a hands-on background in Python and enterprise AI delivery.

The role involves solutioning, architecture, and development of complex AI platforms across business domains. The ideal candidate has 8+ years of software/AI/ML/architecture experience, strong knowledge of LLM orchestration frameworks, vector databases, and cloud platforms (AWS/Azure/GCP).