Senior Agentic AI Engineer

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🕒 March 6

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Rayda

WebsiteLinkedInAll Job Openings

11 - 50 employees

☁️ SaaS

🤝 B2B

👥 HR Tech

💰 Pre seed on 2023-02

SaaS • B2B • HR Tech

Rayda is a SaaS platform that automates global employee device lifecycle management for companies. It handles procurement, pre-configuration, international shipping, tracking, maintenance, secure data wiping, retrieval, storage, insurance, and sustainable disposal across 170+ countries, enabling IT, HR, and operations teams to equip remote employees quickly and reliably. Rayda centralizes device tracking and documentation, reduces device-related tickets and costs, and accelerates onboarding and offboarding workflows for distributed, enterprise customers.

📋 Description

• Design, develop, and deploy autonomous AI agents and multi-agent systems for real-world business applications. • Architect agentic workflows that leverage planning, reasoning, memory, tool usage, and autonomous execution. • Build and optimize Retrieval-Augmented Generation (RAG) systems, knowledge retrieval pipelines, and vector database integrations. • Develop scalable agent orchestration frameworks using tools such as LangGraph, CrewAI, AutoGen, OpenAI Agents SDK. • Integrate AI agents with internal systems, APIs, databases, enterprise platforms, and third-party tools. • Implement agent evaluation, monitoring, observability, and guardrail mechanisms to ensure reliability and safety. • Collaborate with product, engineering, and business teams to identify opportunities for intelligent automation and AI-driven innovation. • Drive technical leadership, architectural decisions, and AI best practices across the organization.

🎯 Requirements

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field. • 7+ years of software engineering experience, including experience building scalable distributed systems. • 3+ years of hands-on experience developing and deploying AI/ML solutions in production. • Strong proficiency in Python and modern AI development frameworks. • Demonstrated experience building AI agents, autonomous workflows, and agent orchestration systems. • Expertise in Large Language Models (OpenAI, Anthropic, Gemini, Llama, Mistral, or equivalent). • Strong understanding of prompt engineering, tool calling, function execution, memory systems, and agent planning strategies. • Experience with vector databases, embeddings, semantic search, and Retrieval-Augmented Generation (RAG). • Strong knowledge of APIs, microservices, CI/CD pipelines, Docker, and MLOps practices.