Agentic AI Developer

Overview

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, Lang Chain, 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.

• 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, Lang Chain, 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

• 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

• Experience with Semantic Kernel, Lang Chain, 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 App Sec best practices

• Agentic AI development
• Generative AI & LLM integration
• Prompt engineering & tool orchestration
• Retrieval-Augmented Generation (RAG)
• Python / C#
• REST APIs & microservices
• Cloud platforms (Azure preferred)