Senior Agentic AI Engineer

LLangGraph

REMOTE · WORLDWIDE

$53K–$78K

Full-time

SENIOR

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About the Role

Rayda is seeking a Senior Agentic AI Engineer to design and deploy autonomous AI systems. The role involves building LLM-based agents, multi-agent architectures, and RAG pipelines. You will lead AI strategy and work with LangGraph, CrewAI, and AutoGen.

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.

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.

L

LangGraph

San Francisco · US · 265+ employees

LangGraph is not a separate company, but an open-source agent orchestration framework and runtime library developed by LangChain Inc. It is designed for building, managing, and deploying complex, stateful, and long-running AI agent workflows.

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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.

Nice to Have

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.