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

📌 RDE engineer (Bengaluru)
🏢 WSNE Consulting
📍 Bengaluru