RDE engineer

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 environments 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