Agentic AI Developer
Vibotek LLC
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Atlanta, GA
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Not Applicable
Posted March 30, 2026
2 variants
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Responsibilities
Responsibilities
- Develop agentic AI applications that autonomously plan, reason, and execute tasks across enterprise environments
- Implement multi-agent workflows using modern agent orchestration frameworks (e.g., Semantic Kernel, LangChain, or similar)
- Design and develop Retrieval-Augmented Generation (RAG) and knowledge-grounded AI solutions
- Integrate AI agents with enterprise systems via REST APIs, databases, and cloud services
- Build agent memory, tool usage, and prompt workflows for reliable and repeatable execution
- Collaborate with product, cloud, and application teams to embed AI agents into business platforms
- Optimize AI solutions for performance, security, compliance, and cost efficiency
- Support testing, monitoring, and continuous improvement of deployed AI agents
Not Met Priorities
What still needs stronger evidence
Requirements
- 5+ years of software or AI/ML development experience
- 2+ years of hands-on experience with Generative AI and agent-based systems
- Strong experience with Agentic AI concepts: planning, memory, tools, and autonomous execution
- Proficiency in Python and/or C# for AI application development
- Experience working with LLMs, prompt engineering, and model APIs
- Hands-on experience with RAG pipelines, vector databases, and embeddings
- Familiarity with cloud-native architectures and RESTful integrations
- Python / C#
- REST APIs & microservices
- Cloud platforms (Azure preferred)
Preferred Skills
- Experience with Semantic Kernel, LangChain, or similar agent frameworks
- Exposure to Azure OpenAI, OpenAI APIs, or equivalent LLM platforms
- Understanding of MLOps, model lifecycle management, and AI monitoring
- Experience delivering AI solutions in enterprise or regulated environments
- Knowledge of secure AI deployment and AppSec best practices
- Technical Skills
- Agentic AI development
- Generative AI & LLM integration
- Prompt engineering & tool orchestration
- Retrieval-Augmented Generation (RAG)
- Python / C#
- REST APIs & microservices
- Cloud platforms (Azure preferred)
Key Responsibilities
Develop agentic AI applications that autonomously plan, reason, and execute tasks across enterprise environments
Implement multi-agent workflows using modern agent orchestration frameworks (e.g., Semantic Kernel, LangChain, or similar)
Design and develop Retrieval-Augmented Generation (RAG) and knowledge-grounded AI solutions
Integrate AI agents with enterprise systems via REST APIs, databases, and cloud services
Build agent memory, tool usage, and prompt workflows for reliable and repeatable execution
Collaborate with product, cloud, and application teams to embed AI agents into business platforms
Optimize AI solutions for performance, security, compliance, and cost efficiency
Support testing, monitoring, and continuous improvement of deployed AI agents
Required Qualifications
5+ years of software or AI/ML development experience
2+ years of hands-on experience with Generative AI and agent-based systems
Strong experience with Agentic AI concepts: planning, memory, tools, and autonomous execution
Proficiency in Python and/or C# for AI application development
Experience working with LLMs, prompt engineering, and model APIs
Hands-on experience with RAG pipelines, vector databases, and embeddings
Familiarity with cloud-native architectures and RESTful integrations
Preferred Qualifications
Experience with Semantic Kernel, LangChain, or similar agent frameworks
Exposure to Azure OpenAI, OpenAI APIs, or equivalent LLM platforms
Understanding of MLOps, model lifecycle management, and AI monitoring
Experience delivering AI solutions in enterprise or regulated environments
Knowledge of secure AI deployment and AppSec best practices
Technical Skills
Agentic AI development
Generative AI & LLM integration
Prompt engineering & tool orchestration
Retrieval-Augmented Generation (RAG)
Python / C#
REST APIs & microservices
Cloud platforms (Azure preferred)
Develop agentic AI applications that autonomously plan, reason, and execute tasks across enterprise environments
Implement multi-agent workflows using modern agent orchestration frameworks (e.g., Semantic Kernel, LangChain, or similar)
Design and develop Retrieval-Augmented Generation (RAG) and knowledge-grounded AI solutions
Integrate AI agents with enterprise systems via REST APIs, databases, and cloud services
Build agent memory, tool usage, and prompt workflows for reliable and repeatable execution
Collaborate with product, cloud, and application teams to embed AI agents into business platforms
Optimize AI solutions for performance, security, compliance, and cost efficiency
Support testing, monitoring, and continuous improvement of deployed AI agents
Required Qualifications
5+ years of software or AI/ML development experience
2+ years of hands-on experience with Generative AI and agent-based systems
Strong experience with Agentic AI concepts: planning, memory, tools, and autonomous execution
Proficiency in Python and/or C# for AI application development
Experience working with LLMs, prompt engineering, and model APIs
Hands-on experience with RAG pipelines, vector databases, and embeddings
Familiarity with cloud-native architectures and RESTful integrations
Preferred Qualifications
Experience with Semantic Kernel, LangChain, or similar agent frameworks
Exposure to Azure OpenAI, OpenAI APIs, or equivalent LLM platforms
Understanding of MLOps, model lifecycle management, and AI monitoring
Experience delivering AI solutions in enterprise or regulated environments
Knowledge of secure AI deployment and AppSec best practices
Technical Skills
Agentic AI development
Generative AI & LLM integration
Prompt engineering & tool orchestration
Retrieval-Augmented Generation (RAG)
Python / C#
REST APIs & microservices
Cloud platforms (Azure preferred)