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 ResponsibilitiesDesign, 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.
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.
Required QualificationsBachelor'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.
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 QualificationsExperience 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.
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.
What You'll BuildAutonomous 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.
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.
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