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Niche agentic AI skills and seniority significantly reduce applicant competition.
Highly specialized agentic AI, LLM orchestration, and platform integrations limit cross-industry transferability.
Explicit 9–12 years, mandatory 3+ years applied AI, and required LangChain/MCP/Azure skills make shortlisting highly strict.
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Design and deliver end-to-end AI solutions including multi-agent systems, AI integrations, and automation workflows for clients and internal use.
Engage with US-based clients as the technical AI SME, managing discovery sessions, workshops, and solution reviews to ensure delivery of production-grade AI solutions.
Support organizational AI adoption by designing governance frameworks, enablement materials, and mentoring junior AI engineers, while continuously evaluating emerging AI technologies.
9–12 years of professional experience in software engineering, solution architecture, or technology consulting.
Minimum 3 years of applied AI/GenAI engineering or architecture experience in production environments; POC or academic-only work not accepted.
Hands-on production experience with LangChain and LangGraph; MCP design and implementation experience required.
Experience with Python programming, LLM API integrations (OpenAI, Anthropic, Azure), vector databases (Pinecone, ChromaDB, FAISS), and Azure AI platform tools (Azure AI Foundry, Azure OpenAI Service, Power Automate).
Proven track record of delivering measurable business outcomes through AI solutions in client-facing roles with distributed delivery experience.
Strong expertise in agentic AI architectures and multi-agent frameworks, capable of designing scalable, context-aware automation pipelines.
Experience mentoring junior engineers and collaborating with enterprise architects to align AI solutions with broader organizational technology standards.