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Mid-level LLM role with moderate brand signal but niche MCP/RAG expertise reduces broad applicant density.
Requires specialized LLM, RAG, MCP, and responsible-AI skills, so applicants from other domains fit poorly.
Explicit 6+ years plus many mandatory LLM, RAG, MCP, guardrails, and productionization requirements.
Design, develop, and deploy enterprise-grade AI tools leveraging LLMs, AI agents, and multi-model AI ecosystems including Copilot, Claude, OpenAI, Anthropic, Microsoft, Google, and Meta.
Implement and maintain AI Guardrails for application safety, compliance, responsible AI usage, security, and governance, including monitoring and feedback mechanisms in production environments.
Develop and optimize Retrieval Augmented Generation (RAG) pipelines, Context Compression strategies, and MCP Server-based solutions to enable scalable, cost-efficient, and performant AI experiences.
6+ years of professional experience in AI/ML development, software engineering, or testing with hands-on experience in production AI applications.
Proficiency with LLM-based platforms such as Copilot, Claude, OpenAI GPT models, Anthropic APIs, and Microsoft Copilot.
Strong technical skills in RAG implementation, AI Guardrails design, Context Compression/token optimization, and MCP Server integration.
Work Experience Required: 6+ years
Experienced in deploying and managing productionized AI solutions at scale with governance, observability, and responsible AI frameworks.
Demonstrated expertise in multi-model AI ecosystems and integrating AI agents and assistant frameworks within enterprise settings.
Strong knowledge of AI ethics, security, compliance, bias mitigation, and regulatory requirements relevant to AI deployments.