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Exavalu
Digital Transformation Consulting
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This is a remote position.
Experience: 12+ Years | Type: Full-Time
We are seeking a hands-on AI Technical Architect with strong experience in Generative AI and Multi-Agentic AI to design and implement enterprise AI solutions from POC through production. The role requires expertise in agent orchestration, RAG, LLMs, enterprise integrations, cloud, and AI governance.
Design Multi-Agentic AI architectures using agents, supervisors, planners, routers, and orchestration frameworks.
Build AI solutions using Python, LangChain, LangGraph, CrewAI, and LLM APIs.
Design RAG solutions, including embeddings, vector search, retrieval, and prompt optimization.
Integrate AI agents with enterprise applications, APIs, databases, and tools.
Design scalable cloud-native AI solutions using microservices, Docker, and Kubernetes.
Establish AI security, governance, observability, evaluation, and LLMOps/MLOps practices.
Lead POCs, architecture reviews, technical decisions, and mentor AI engineering teams.
12+ years of overall technology experience.
Strong hands-on experience with Generative AI and Multi-Agentic AI.
Advanced Python programming.
Strong hands-on experience with LangChain and LangGraph.
Experience with CrewAI or similar agent frameworks.
Strong knowledge of LLMs, RAG, embeddings, vector databases, prompt engineering, and tool/function calling.
Experience with APIs, microservices, and enterprise integrations.
Experience with Azure, AWS, or GCP.
Strong understanding of AI security, Responsible AI, governance, and guardrails.
MCP and agent interoperability.
Hugging Face / Open-source LLMs.
LangSmith, Langfuse, MLflow, or OpenTelemetry.
Docker/Kubernetes and LLMOps/MLOps.
Semantic Kernel, AutoGen, or similar frameworks.
Knowledge graphs/graph databases.
Experience building enterprise AI platforms or AI Centers of Excellence.
Core Skills: Multi-Agentic AI | Generative AI | LangChain | LangGraph | CrewAI | Python | RAG | LLMs | MCP | Vector Databases | Cloud
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