Agentic AI Engineer / Developer – Python
Summary
Builds and ships autonomous AI agents and multi-agent workflows for enterprise process automation, using Python, LLMs, agent orchestration frameworks, APIs, and cloud AI platforms. Also covers retrieval/memory grounding, monitoring agents in production, and applying responsible-AI governance.
About the role
We are looking for an Agentic AI Engineer with strong hands-on experience in Agentic AI and Python to design, develop, and deploy autonomous AI agents and multi-agent systems. The role focuses on building intelligent workflows using Large Language Models (LLMs), agent orchestration frameworks, APIs, knowledge bases, and cloud AI platforms to automate enterprise processes and improve operational efficiency.
Key responsibilities
Design, develop, and deploy Agentic AI solutions using LLMs and AI agent frameworks.
Build autonomous agents capable of reasoning, planning, tool usage, and multi-step task execution.
Develop and orchestrate multi-agent workflows and AI-driven systems.
Integrate AI agents with enterprise applications, APIs, databases, and cloud services.
Implement memory, context management, retrieval, and knowledge-grounding capabilities.
Develop AI-powered automation solutions for business processes and operational workflows.
Apply Responsible AI principles, governance, security, and compliance controls.
Test, evaluate, monitor, and optimize AI agents in production environments.
Collaborate with business stakeholders to identify and implement Agentic AI use cases.
Develop technical documentation, reusable frameworks, and best practices for AI agent development.
About you
5–7 years of relevant software engineering or AI development experience.
Strong hands-on proficiency in Python.
Practical experience designing and developing Agentic AI solutions.
Experience with LLMs and AI agent orchestration frameworks.
Understanding of autonomous agents, reasoning, planning, and tool calling.
Experience integrating AI solutions with APIs, databases, and enterprise applications.
Knowledge of retrieval, memory, context management, and knowledge grounding.
Strong technical problem-solving and analytical skills.
Excellent communication and collaboration skills.
Experience developing multi-agent systems and complex AI workflows (good-to-have).