Gen AI Developer

Role & responsibilities

Technical Skills Mandatory

• 5+ years of software development experience with strong Python skills.
• Hands-on experience with Azure AI Foundry / Microsoft Foundry.
• Strong experience developing Generative AI and LLM-based applications.
• Hands-on experience with Azure OpenAI / Azure-hosted foundation models.
• Strong knowledge of Prompt Engineering and prompt optimization.
• Experience implementing RAG (Retrieval-Augmented Generation) solutions.
• Experience with Azure AI Search / vector search / semantic search.
• Experience with embeddings and vector databases.
• Hands-on experience developing AI Agents / Agentic AI solutions.
• Experience with frameworks such as LangChain, Semantic Kernel, or LlamaIndex.
• Experience integrating AI solutions with REST APIs, enterprise applications, databases, and document repositories.
• Strong SQL and data processing skills.
• Experience with Git, CI/CD, Docker, and cloud deployment.
• Understanding of LLM evaluation, hallucination reduction, guardrails, and responsible AI.
• Understanding of AI security, including prompt injection, data leakage prevention, authentication, authorization, and secure API integration.
• Experience with application monitoring, logging, performance optimization, and LLM/token cost monitoring.

Technical Skills (Must Have)

• 5+ years of software development experience with strong hands-on expertise in Python.
• Strong hands-on experience in Generative AI and LLM application development.
• Proven experience with Azure AI Foundry / Microsoft Foundry and Azure OpenAI.
• Strong hands-on experience building RAG-based applications using Azure AI Search, embeddings, vector search, and vector databases.
• Experience developing and integrating AI Agents / Agentic AI solutions.
• Strong understanding of Prompt Engineering, LLM evaluation, response optimization, and AI guardrails.
• Experience with LangChain, Semantic Kernel, LlamaIndex, or equivalent GenAI frameworks.
• Experience integrating GenAI applications with REST APIs, enterprise applications, databases, and document/knowledge repositories.
• Strong knowledge of SQL, data processing, Git, CI/CD, and cloud deployment.
• Understanding of AI security and Responsible AI, including prompt injection, data protection, authentication, authorization, and secure API integration.
• Experience with production deployment, application monitoring, logging, performance optimization, and LLM/token cost management.
• Ability to develop scalable, secure, reliable, and production-ready GenAI solutions.