Senior Agentic AI Engineer
New
R
RaydaArtificial intelligence
Source API remote eligibility restrictions: United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 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.
- Required Skills
- DockerPythonMicroservicesPrompt EngineeringLLMMLOps
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 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, such as OpenAI, Anthropic, Gemini, Llama, or Mistral.
- 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.
- Strong knowledge of APIs, microservices, CI/CD pipelines, Docker, and MLOps practices.
- Preferred experience with LangGraph, CrewAI, or AutoGen.
- Preferred knowledge of AI governance, security, compliance, and responsible AI practices.
- Preferred experience with knowledge graphs, reinforcement learning, or advanced reasoning architectures.
Responsibilities
- Design, develop, and deploy autonomous AI agents and multi-agent systems for business applications.
- Architect agentic workflows using planning, reasoning, memory, tool usage, and autonomous execution.
- Build and optimize Retrieval-Augmented Generation systems, knowledge retrieval pipelines, and vector database integrations.
- Develop scalable agent orchestration frameworks using tools such as LangGraph, CrewAI, AutoGen, and 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.
- Collaborate with product, engineering, and business teams to identify intelligent automation opportunities.
- Drive technical leadership, architectural decisions, and AI best practices.
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