Lead Python Application Engineer (Agentic AI)

Please share the Lead profiles.

Core Skills (Mandatory):

Key Skills: Excellent in Python, Generative AI, Agentic AI, RAG, Azure / Google Cloud Platform, Vector Databases, Cloud Architecture, Leadership & Mentoring, CI/CD, Terraform, MLOps, Docker, Kubernetes.

AI, Generative AI & Agentic AI Skills:

• Expertise in Python, hands-on experience in prompt engineering and AI-driven workflow automation.
• Understanding of AI Agent Architectures – Knowledge of multi-agent systems, reasoning loops (e.g., ReAct, Reflexion), and goal-driven AI design.
• Tool Integration & Orchestration – Ability to connect LLMs with external tools, APIs, and data sources for autonomous task execution.
• Framework Proficiency – Hands-on experience with frameworks like LangChain, LangSmith, LlamaIndex, CrewAI, or similar agent orchestration tools.
• Memory & Context Management – Implementing short-term and long-term memory for agents to maintain context across interactions.
• Safety & Control Mechanisms – Designing guardrails, validation layers, and human-in-the-loop controls to ensure safe, predictable agent behavior.
• System Design & Scalability – Architecting agent systems that can scale, coordinate multiple agents, and integrate with enterprise infrastructure.
• Evaluation & Optimization – Measuring agent performance, reasoning accuracy, and optimizing for efficiency and reliability.
• Ability to integrate Generative AI capabilities into enterprise applications.
• Experience with cloud platforms (Azure/ Google Cloud).
• Knowledge of Terraform, containerization using Docker/Kubernetes; and CI/CD automation for scalable, secure, and maintainable deployment of AI services
• Knowledge of NLP, semantic search, and multi-turn conversation design.
• Exposure to multimodal AI systems
• Knowledge of AI orchestration tools and RAG (Retrieval-Augmented Generation) techniques.
• AI Orchestration framework (e.g. Semantic Kernel, AutoGen, Langchain, LangGraph etc.)

Backend & API Development

• API development and integration with enterprise systems.
• Advanced proficiency in Python, multithreading
• Good knowledge of FastAPI
• Secure API development using OAuth2, API Gateway, IAM, RBAC
• Expertise in REST, JSON, and event-driven design.
• Familiarity with GraphQL and asynchronous messaging.

Cloud & DevOps

• Hands-on experience with Azure (and Google Cloud).
• Proficient in Docker and Kubernetes for containerization.

Skills (Good to have):

Streaming & Messaging

• Working knowledge of Redis, Apache Kafka or similar platforms would be an added advantage