Agentic AI Developer

About the Role:

Agentic AI Developer

Key Responsibilities:

• Design and Develop Agentic Systems:

• Architect and implement autonomous agents using Crew AI, LangGraph, LlamaIndex, and

  Copilot Studio

  .
• Build multi-agent workflows with dynamic role assignment and inter-agent communication.

• Use Case Development:

• Ideate, prototype, and deploy agentic AI use cases across domains such as customer support, research automation, enterprise productivity, and decision intelligence.
• Translate business requirements into agentic workflows that deliver measurable outcomes.

• Integration and Orchestration:

• Integrate agents with external APIs, databases, and enterprise systems.
• Orchestrate agent behavior using LangGraph or similar graph-based execution frameworks.

• Knowledge Management:

• Implement RAG pipelines using LlamaIndex or vector databases.
• Enable agents to access and act on structured and unstructured knowledge sources.

• Tool and Memory Management:

• Equip agents with tool-use capabilities (e.g., web search, code execution, file handling).
• Design memory systems for agents to retain context and improve over time.

• Prompt Engineering and Optimization:

• Craft effective prompts and system instructions to guide agent behavior.
• Continuously refine prompts and agent configurations for optimal performance.

• Monitoring and Evaluation:

• Set up logging, tracing, and evaluation metrics to monitor agent performance.
• Conduct A/B testing and iterative improvements based on analytics and feedback.

• Collaboration and Documentation:

• Work closely with product managers, data scientists, and engineers to align agentic solutions with business goals.
• Document agent architectures, workflows, and implementation details.

• Research and Innovation:

• Stay current with advancements in agentic AI, LLMs, and autonomous systems.
• Experiment with emerging frameworks and contribute to internal R&D initiatives.

Required Skills & Qualifications:

• Proven experience developing agentic AI use cases using

  Crew AI

  ,

  LlamaIndex

  ,

  LangGraph

  ,

  Copilot Studio

  , or similar frameworks.
• Strong proficiency in

  Python

  , including experience with AI/ML libraries such as TensorFlow, Pytorch, Pandas, NumPy etc.
• Deep understanding of LLMs (e.g., GPT, Claude, Mistral) and their integration into agentic workflows.
• Experience with vector databases, RAG, and knowledge graphs.
• Ability to design multi-agent systems with clear roles, communication protocols, and task orchestration.
• Familiarity with prompt engineering, tool calling, and memory management in agentic systems.
• Excellent problem-solving skills and ability to work independently or in a team environment.

Preferred Qualifications:

• Experience with real-world deployments of agentic AI in domains such as customer support, research automation, or enterprise workflows.
• Contributions to open-source agentic AI projects or publications in the field.
• Knowledge of reinforcement learning, planning algorithms, or cognitive architectures.