> Markdown version of [/jobs/ext/4181793-ai-technical-architect](https://www.wearedevelopers.com/jobs/ext/4181793-ai-technical-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Technical Architect - **Company:** SRS Consulting Inc - **Location:** San Jose, CA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Databases, Python (Programming Language), Machine Learning, Natural Language Processing, Google Cloud, Enterprise Software Applications, LangChain, Retrieval-Augmented Generation, Large Language Models, Agentic-AI, Kubernetes, Semantic Kernel - **Published:** October 2, 2026 - **Apply:** https://www.dice.com/job-detail/fe352d2b-090c-440a-bca5-5a04a8412863 ## About the Role * 8+ years of software/AI/ML/architecture experience. * Strong hands-on experience with LLMs, GenAI, RAG, and Agentic AI. * Strong Python development experience. * Machine Learning and NLP experience. * Experience with LLM orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, or similar. * Experience with vector databases and embeddings. * Strong solution architecture and technical solutioning experience. * Experience with AWS, Azure, or Google Cloud Platform. * Excellent communication and stakeholder management skills. ## Description We are seeking an experienced AI Technical Architect with a strong hands-on background in GenAI, LLMs, RAG, Agentic AI, Machine Learning, NLP, Python, and AI Solution Architecture. The candidate will be responsible for solutioning, architecture, and development of enterprise AI solutions., * Design and architect enterprise GenAI, LLM, RAG, and Agentic AI solutions. * Work with business and technical stakeholders to understand requirements and develop AI solutions. * Lead technical solutioning, architecture, 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.