Senior Agentic AI Solution Architect
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Role details
Tech stack
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Job description
We are seeking a Senior Agentic AI Solution Architect to design and deliver enterprise AI applications, intelligent assistants, and automated workflows. You will translate business requirements into secure, scalable solutions and guide engineering teams from proof of concept through production., * Design AI solutions using large language models (LLMs), AI agents, and multi-agent workflows.
- Build solution designs covering agent orchestration, memory, tool integration, and human approval steps.
- Design Retrieval-Augmented Generation (RAG) pipelines to connect AI applications with enterprise knowledge.
- Integrate AI agents with APIs, databases, and business applications using Model Context Protocol (MCP) and other integration methods.
- Select suitable models, frameworks, and cloud services based on business needs, performance, and cost.
- Define security controls, testing, monitoring, and deployment requirements.
- Create architecture documentation and provide technical guidance to development teams.
Requirements
- 10+ years of IT experience, including 4+ years in solution or technical architecture.
- 3+ years in Generative AI, LLMs, or AI application development, including 2+ years designing or delivering Agentic AI solutions.
- Experience taking AI applications from proof of concept to production.
- Hands-on experience with one or more agent frameworks, such as LangGraph, LangChain, Semantic Kernel, AutoGen, or CrewAI.
- Strong knowledge of RAG, embeddings, vector databases, prompt engineering, and context management.
- Experience with MCP servers, clients, and tool integrations.
- Proficiency in Python, TypeScript, Java, or .NET.
- Experience with an AI platform such as Azure OpenAI, AWS Bedrock, or Google Vertex AI.
- Knowledge of API integration, cloud deployment, CI/CD, security, and AI evaluation.
- Strong communication skills and experience working with business and engineering teams., * Experience with enterprise copilots, conversational assistants, or AI workflow automation.
- Integration experience with CRM, ERP, ITSM, or other enterprise systems.
- Knowledge of GraphRAG, knowledge graphs, or advanced enterprise search.
- Healthcare experience, including familiarity with HL7/FHIR, EHR integrations, and HIPAA requirements.
Skills
Agentic AI, Solution Architecture, Generative AI, LLM, Multi-Agent Systems, LangGraph, LangChain, Semantic Kernel, AutoGen, CrewAI, MCP, RAG, Prompt Engineering, Context Engineering, Vector Databases, Python, TypeScript, Azure OpenAI, AWS Bedrock, Google Vertex AI, REST APIs, CI/CD, AI Security, LLMOps
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