GenAI Solution Architect — Remote & AI-DLC Expert

Exavalu; California; Hybrid; USD 150,000 - 230,000; Full time

Job summary

Exavalu is seeking a Solution Architect with deep GenAI, Claude, and LLM experience to drive AI-enabled software delivery and modernization. This remote, full-time role requires leading technical teams and translating business needs into scalable architectures.

You will design secure solutions, integrate AI across lifecycle stages, and ensure governance and responsible AI practices while collaborating with clients and stakeholders across functions.

Qualifications

• Strong experience in Solution or Enterprise Architecture.
• Hands-on knowledge of Claude/Claude Code, GenAI, and LLM-based solutions.
• Understanding of agentic AI patterns and AI-DLC practices.
• Strong cloud, API, microservices, and integration architecture skills.
• Excellent client communication and technical leadership abilities.
• Experience with multi-agent systems and LLM orchestration.
• Exposure to AWS, Azure, or GCP.
• Experience with AI-assisted coding, automated testing, and application modernization.

Responsibilities

• Design secure, scalable enterprise solutions leveraging GenAI and agentic AI.
• Integrate AI across requirements, design, development, testing, modernization, and support.
• Translate business needs into technical architecture and solution designs.
• Lead technical teams and drive AI-led productivity improvements.
• Knowledge of enterprise security, governance, and responsible AI.

Skills

Solution Architecture

Enterprise Architecture

Claude/Claude Code

GenAI

LLM Solutions

Agentic AI

Cloud Architecture

APIs & Microservices

Technical Leadership

Client Communication

Job description

Exavalu is seeking a Solution Architect with deep GenAI, Claude, and LLM experience to drive AI-enabled software delivery and modernization. This remote, full-time role requires leading technical teams and translating business needs into scalable architectures.

You will design secure solutions, integrate AI across lifecycle stages, and ensure governance and responsible AI practices while collaborating with clients and stakeholders across functions.