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Protocol Intelligence
Data-driven signals on your job's competitivenessStrong Tier-1 brand, metro location, mid-level generalist title and hot GenAI skills attract many applicants.
Core GenAI, RAG, and agent engineering skills transfer across industries, though enterprise banking experience modestly preferred.
Multiple mandatory technical requirements (Python, GenAI, RAG, LLM integration) enforce strict filters.
Job Description
Structured overview of role & requirementsAbout This Role
Lead design and development of an agentic AI platform enabling business users to configure and manage AI agents without deep technical expertise.
Architect and build complex multi-agent AI systems with capabilities including multi-step planning, tool use, memory, and autonomous task execution using frameworks like LangGraph and DeepAgents SDK.
Drive integration and optimization of Retrieval-Augmented Generation (RAG) pipelines and Generative AI/LLM capabilities within scalable backend services, ensuring production-grade scalability, reliability, and observability.
Minimum Requirements
5+ years of software engineering experience (work experience demonstrated via work, training, education, or military experience).
Strong hands-on Python expertise.
Proven experience building AI/Generative AI (GenAI) applications in production environments.
Experience with RAG architectures (embeddings, vector databases, chunking strategies) and agentic AI systems (multi-agent orchestration, planning, tool-calling, memory management).
Ideal Candidate Profile
Experienced in architecting and leading large-scale technology projects with companywide impact and setting engineering best practices.
Familiar with advanced AI integration patterns including prompt engineering, LLM integration, and RAG pipeline design in fast-evolving AI product environments.
Able to mentor junior engineers and collaborate across product, architecture, and business teams to translate automation solutions into scalable AI agent platforms.