Bebo Technologies - Agentic AI Architect

Description

• 9 to 12 years of experience in software architecture, backend systems, or AI platform development.
• Strong proficiency in Python and familiarity with design patterns and microservices architectures.
• Hands-on experience with LLMs and agent frameworks such as LangChain, LangGraph, CrewAI, AutoGen, and AutoGPT or similar.
• Expertise in embeddings, vector databases, and retrieval systems.
• Proven track record of designing scalable and maintainable systems.
• Design and scale RAG architectures, including strategies for retrieval, grounding mechanisms, and data flow patterns.
• Evaluate and select LLMs, agent frameworks, and orchestration tools based on performance, cost, and use-case fit.
  

Job Summary

Key Responsibilities

• Design and architect scalable, maintainable AI platforms and backend systems.
• Lead the design and implementation of RAG architectures, including retrieval strategies, grounding mechanisms, and data flow patterns.
• Architect microservices-based systems to support AI/LLM workloads.
• Evaluate, select, and integrate LLMs, agent frameworks, and orchestration tools based on performance, cost, security, and business use cases.
• Design systems leveraging embeddings, vector databases, and retrieval pipelines.
• Build and optimize AI workflows using agent frameworks such as LangChain, LangGraph, CrewAI, AutoGen, AutoGPT, or similar tools.
• Collaborate with product, data, and engineering teams to translate business requirements into technical architectures.
• Establish best practices for system design, reliability, scalability, and maintainability.
• Provide technical leadership, architecture reviews, and mentorship to engineering teams.
• Stay up to date with emerging trends in LLMs, AI agents, and AI infrastructure.
  

Required Skills & Qualifications

Core Technical Skills :

• 9- 12 years of experience in software architecture, backend systems, or AI platform development.
• Strong proficiency in Python for backend and AI application development.
• Deep understanding of design patterns, system design, and microservices architectures.
• Hands-on experience with LLMs and agent frameworks such as :
• LangChain
• LangGraph
• CrewAI
• AutoGen
• AutoGPT (or similar)
• Expertise in embeddings, vector databases, and information retrieval systems.