Role & responsibilities
Design and develop Agentic AI solutions and AI-powered enterprise applications.
Build AI agents, workflows, orchestration, and automation using LLMs and Python.
Develop and optimize RAG (Retrieval-Augmented Generation) solutions.
Perform LLM/prompt engineering and integrate AI models with enterprise applications.
Develop scalable Python-based APIs, services, and microservices.
Integrate AI solutions with enterprise platforms, databases, APIs, and third-party systems.
Deploy AI applications on cloud-native settings such as AWS, Azure, or GCP.
Implement CI/CD pipelines, DevOps practices, containerization, and automated deployment.
Build testing frameworks and perform functional, integration, and performance testing for AI applications.
Implement observability, monitoring, logging, tracing, and performance management for AI/ML workloads.
Apply security, responsible AI, data protection, and governance principles.
Troubleshoot production issues and support enterprise-scale AI deployments.
Collaborate with architects, developers, data scientists, DevOps teams, and business stakeholders.

Mandatory Skills

📌 Rde Engineer Gurugram
🏢 WSNE Consulting
📍 Gurugram