Job Title: Generative AI / Agentic AI Architect

Location: Houston, TX (Preferred) /

Duration: Long-Term Contract

Job Summary

We are seeking an experienced Generative AI / Agentic AI Architect to design, develop, and implement enterprise-scale AI solutions leveraging Large Language Models (LLMs), Agentic AI frameworks, and advanced AI orchestration platforms. The ideal candidate will have deep expertise in building autonomous AI agents, AI-powered workflows, and coding assistants using technologies such as Claude Code, OpenAI, LangChain, LangGraph, and related AI frameworks.

Key Responsibilities

• Architect and develop enterprise-grade Generative AI and Agentic AI solutions.
• Design and implement autonomous AI agents capable of planning, reasoning, tool usage, and workflow orchestration.
• Build AI-powered applications utilizing Claude Code, OpenAI, Anthropic Claude, and other LLM platforms.
• Develop multi-agent systems using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar technologies.
• Create Retrieval-Augmented Generation (RAG) solutions leveraging vector databases and knowledge management systems.
• Collaborate with business stakeholders to identify AI use cases and translate requirements into scalable architectures.
• Design secure, scalable, and cost-effective AI infrastructure on cloud platforms.
• Establish AI governance, observability, monitoring, and security best practices.
• Mentor development teams and provide technical leadership for AI initiatives.

Required Skills

• 12+ years of software engineering experience with at least 3+ years in Generative AI.
• Strong hands-on experience with Agentic AI and AI orchestration frameworks.
• Experience building solutions using Claude Code, Anthropic Claude, OpenAI GPT, Gemini, or similar LLM platforms.
• Expertise with LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or equivalent frameworks.
• Strong programming skills in Python.
• Experience with RAG architectures, vector databases, embeddings, and prompt engineering.
• Knowledge of AI model deployment, MLOps, and cloud-native architectures.
• Experience with AWS, Azure, or Google Cloud Platform.
• Strong understanding of AI security, governance, and responsible AI practices.
• Excellent communication and stakeholder management skills.