Gen AI Engineer with Python | Consultant / Senior Consultant
HybridShaikpet, State of Telangāna, Republic of India
Job Summary
Design, develop, and enhance enterprise AI and Generative AI solutions using Python, focusing on building intelligent Agentic AI applications capable of autonomous task execution. Implement Retrieval-Augmented Generation (RAG) solutions, orchestrate multi-agent architectures with LangGraph, and integrate agents using Model Context Protocol (MCP) and tool-calling frameworks. Optimize, debug, test, and deploy scalable AI applications for enterprise environments while managing experiment tracking and model lifecycles with MLflow. Collaborate with cross-functional Agile teams to translate business requirements into AI-enabled solutions and contribute to architecture discussions. This role requires 8+ years of experience and is available in Hyderabad, Bengaluru, Pune, or Chennai on a hybrid basis.
Required Qualifications
- 8+ Years of experience
- Strong hands-on experience in Python Development
- Excellent understanding of Artificial Intelligence and Generative AI
- Experience designing and building Agentic AI Solutions
- Hands-on experience with Python ADK or similar agent development frameworks
- Strong knowledge of Prompt Engineering
- Experience defining agent behaviors, instructions, and interaction patterns
- Experience implementing Agentic Workflows and orchestration frameworks
- Working knowledge of Model Context Protocol (MCP)
- Experience implementing Retrieval-Augmented Generation (RAG)
- Hands-on experience with MLflow or similar ML lifecycle management tools
- Experience using LangGraph or graph-based orchestration frameworks
- Strong debugging and problem-solving skills
- Experience working in Agile development environments
Desired Qualifications
- Experience with PySpark
- Knowledge of Big Data ecosystems
- Experience with Data Engineering
- Cloud platform experience (Azure, AWS, or GCP)
- MLOps exposure
- Experience building scalable AI data pipelines
- Experience deploying enterprise AI applications in production
- Knowledge of distributed AI workloads
- Kubernetes (Preferred)
- Azure/AWS/GCP (Preferred)
- REST APIs
- Git
- Docker
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