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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:
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.
- 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 Google Cloud Platform).
- 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.