Lead AI Security Engineer

6 days ago

kannur, India beBeeSecurity Full time

Job DescriptionWe are seeking a Senior AI Architect to lead our efforts in building a cutting-edge enterprise security platform. The successful candidate will be responsible for designing and scaling agentic RAG and text-to-SQL copilots capable of handling high volumes of daily queries with exceptional reliability and semantic accuracy.The ideal candidate will have strong Python engineering skills, hands-on experience with RAG, agent architectures, tool-calling, and text-to-SQL copilots, as well as proven expertise in MCP servers, vector databases, and retrieval-augmented architectures.This role requires a collaborative mindset with the ability to work closely with cross-functional teams, including product, infrastructure, and leadership, to deliver enterprise-grade features and meet business objectives.Key Responsibilities:Design and Scale Agentic Solutions: Develop and maintain agentic RAG and text-to-SQL copilots to handle high volumes of daily queries with 99.9%+ reliability and high semantic accuracy.Build and Optimize Infrastructure: Construct, maintain, and optimize our LLMOps stack using tools like LangGraph, LangSmith, MLflow, Kubernetes, async inference, and cloud LLM providers such as AWS Bedrock, Google Vertex, Azure OpenAI, Anthropic, etc.Maintain Server Integrations: Develop and maintain MCP server integrations to ensure robust and efficient runtime execution across agents and tools.Implement Evaluation Frameworks: Design and implement evaluation frameworks and guardrails to minimize hallucinations, reduce drift, and cut token/cost overhead by ~30%.Own System Observability: Own system observability & performance, including latency, throughput, cost optimization, caching, and retrieval quality.Requirements:5+ years in software or ML engineering, including production-grade LLM or RAG systems.Strong Python engineering skills and hands-on experience with RAG, agent architectures, tool-calling, and text-to-SQL copilots.Proven experience with MCP servers, vector databases, and retrieval-augmented architectures.Expertise in agent development, LLM integration workflows, prompt engineering, and runtime orchestration systems.Hands-on with container orchestration and infra: Kubernetes, async workers, queueing systems, observability stacks, etc.

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