Description review
Senior Agentic AI Engineer
Rayda · United States · back to the listing
HR standards
62/100
needs work
Title ↔ description
84/100
solid
Reads as
Machine Learning Engineer
95% confident
What this role officially is
data scientist — ESCO, the EU occupation classification
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist
How others title the same work
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Startups
- Attendi | Medior Machine Learning Engineer | Amsterdam, Netherlands | ONSITE (hybrid) | €6,000 - €7,000 per month | Full-time (80–100%, ~4–5 days/week) | Visa sponsorship + 30% ruling possible Attendi
- Member of Technical Staff (applied) Anthrogen
- Aptura AI | Full-Time | MTS (Applied AI), MTS (SWE / Product) | London | ONSITE / HYBRID Aptura AI
- Arcforma AI (arcforma.ai) | AI Engineer (Marketing / Construction / Arcforma AI (arcforma.ai)
- Staff AI Engineer - Agent Architecture & Behavior Artisan
What the listing never says
- 26 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
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
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