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Niche LLM/agentic expertise and senior requirement reduce applicant density.
Highly specialized LLM, agentic AI, and vector/knowledge-graph skills limit cross-industry transferability.
Explicit 9+ years plus 3+ years AI/LLM and mandatory specialized tool expertise imposes strict filters.
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Lead design and development of AI-powered, agentic applications utilizing LLMs, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), and agent-based architectures.
Build and optimize autonomous or semi-autonomous AI agents, multi-agent workflows, and MCP-compatible tools integrated with enterprise systems.
Ensure performance, reliability, safety, and scalability of AI-enabled cloud architectures and mentor developers in AI engineering and agentic design patterns.
Bachelor’s degree in Engineering, Computer Science, or equivalent.
9+ years of professional software development experience with at least 3 years focused on AI product development including AI/LLM and agentic systems.
Hands-on experience with Large Language Models (e.g., Azure OpenAI, OpenAI API), RAG, vector databases, prompt engineering, agent frameworks (Semantic Kernel preferred, LangChain, LlamaIndex).
Experience with multi-threading, relational databases (SQL Server, PostgreSQL), cloud platforms (Azure preferred), Python for AI/ML pipelines, familiarity with graph-based systems (Neo4j, Cosmos DB).
Experienced engineer able to deliver production-grade AI systems combining strong software engineering and AI innovation skills.
Expertise in end-to-end intelligent workflow design, autonomous agent architecture, and integration of advanced AI tooling (MCP, multi-agent orchestration).
Comfortable working in Agile environments, collaborating cross-functionally, and mentoring teams on AI engineering and agentic system design.