AI Solution Architect

Job Summary

We are seeking an experienced AI Solution Architect to design and deliver enterprise-grade AI solutions using Python LangChain LangGraph RAG and Agentic AI frameworks. The ideal candidate will work closely with business and engineering teams to architect scalable GenAI applications intelligent agents and AI-powered automation solutions.

Key Responsibilities:

• Design end-to-end AI/GenAI solution architectures for enterprise use cases.
• Build and deploy AI applications using Python LangChain LangGraph and Agentic AI frameworks.
• Develop and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and knowledge repositories.
• Architect multi-agent systems AI workflows and autonomous decision-making solutions.
• Integrate LLMs (OpenAI Anthropic Gemini Llama etc.) with enterprise applications and data platforms.
• Define AI governance security scalability and performance best practices.
• Collaborate with stakeholders to translate business requirements into AI solutions.
• Provide technical leadership design reviews and mentoring to engineering teams.

Required Skills

• 10 - 15 years of software engineering experience with 3 years in AI/GenAI architecture.
• Strong expertise in Python LangChain LangGraph RAG and Agentic AI.
• Experience with LLMs prompt engineering AI orchestration and vector databases.
• Hands-on experience with cloud platforms (AWS Azure or GCP).
• Strong understanding of AI system design APIs microservices and distributed architectures.
• Experience with AI observability evaluation and production deployment.
• Preferred Qualifications
• Experience with AI agents MCP workflow orchestration and enterprise AI platforms.
• Knowledge of MLOps Kubernetes Docker and CI/CD practices.
• Excellent communication and stakeholder management skills.