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Niche AI-agent role but metro location and mid-level experience increase candidate density.
Highly specialized AI agent, RAG, and LLM integration skills limit cross-industry transferability.
Specific LLM, RAG, TypeScript, and integration requirements enforce rigid technical filters.
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Develop and enhance an AI-driven software development lifecycle platform using autonomous agents and tool integrations to automate SDLC phases.
Design and implement Retrieval-Augmented Generation (RAG) pipelines and governance mechanisms for context-aware AI-driven code generation.
Integrate enterprise ALM/DevOps tools and build event-driven hooks, state machines, and self-healing systems to support AI-native SDLC workflows.
4+ years of production-grade experience with TypeScript / Node.js.
Proven experience building or extending multi-step AI agent systems with tool-use and human-in-the-loop patterns.
Experience designing RAG pipelines including embedding, chunking, vector databases, and context injection.
Proficiency with Azure OpenAI or equivalent LLM integration, including prompt engineering and structured outputs.
Experienced in full-stack architecture covering API, queue, database, frontend, and infrastructure design for AI-native systems.
Skilled in workflow or state machine design for lifecycle management and event-driven orchestration within complex software systems.
Familiarity with CI/CD pipeline authoring, containerization (Docker), and enterprise ALM/DevOps tool integration (e.g., Rally, Azure DevOps).