Senior Agentic AI Engineer

This is a remote position. Job Title:Senior Agentic AI Engineer Rayda is looking for an exceptional Senior Agentic AI Engineer to lead the design, development, and deployment of autonomous AI systems that drive intelligent decision-making, workflow automation, and next-generation user experiences. This role is ideal for an engineer with deep expertise in Large Language Models (LLMs), AI agents, multi-agent architectures, orchestration frameworks, and production-grade AI systems. You will play a critical role in defining Rayda's AI strategy and building intelligent agents that can reason, plan, act, and collaborate to solve complex business challenges. Key Responsibilities - 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. What You'll Build - Autonomous AI agents capable of planning, reasoning, and taking actions across enterprise systems. - Multi-agent ecosystems that collaborate to solve complex operational and customer challenges. - Intelligent workflow automation that improves productivity, efficiency, and business outcomes. - Production-ready agentic platforms that scale securely and reliably. Requirements Required Qualifications - 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. Preferred Qualifications - Experience with LangGraph, CrewAI, AutoGen. - Experience designing multi-agent collaboration systems and autonomous decision-making workflows. - Knowledge of AI governance, security, compliance, and responsible AI practices. - Experience with knowledge graphs, reinforcement learning, or advanced reasoning architectures. - Startup or high-growth technology company experience. Originally posted on Himalayas