AI Application Developer

 We're seeking an experienced AI Applications Developer to drive integration of the Generation AI into our data protection & recovery solutions platform. 

You would be building production-grade AI systems that integrate into existing product and leverage Generative AI advancements. You would be responsible for agentic workflows that enable conversational AI, complex process automation and seamless troubleshooting in customer product journey. 

Responsibilities 

• Design, develop, and maintain Generation AI applications and intelligent agents tailored for product needs 

• Write clean & testable code following CI/CD & DevOps best practices. 

• Develop and maintain backend services for AI applications 

• End-to-end solutioning for AI agents and agentic workflows 

• Build effective semantic search systems for LLM application workflows using vector databases and embedding technologies 

• Building LLM integrations for external information with function/tools calling and leveraging latest standards like Model Context Protocol (MCP), agent-to-agent protocol(A2A) 

• Collaborate with cross-functional teams to integrate LLM capabilities into existing products 

• Stay up to date with the latest advancements in Generative AI technologies and best practices 

Requirements 

Core Software Engineering 

• 4+ years of professional software development experience, with a proven track record of shipping production code 

• Strong problem-solving skills, with commitment to write clean, testable and maintainable code 

• Strong proficiency in Python/Go, including a solid understanding of asynchronous programming 

• Experience building and maintaining REST APIs using modern backend frameworks 

• Familiarity with both SQL and NoSQL databases 

Generative AI and LLM expertise 

• Proven experience building applications with LLM development frameworks (E.g. Langchain, LangGraph, Dspy or similar) 

• Demonstrable experience in designing and building AI agentic workflows, including function/tools calling to give LLM access to external information 

• Deep understanding of semantic search concepts, including RAG, vector embeddings, and hands-no experience with vector databases (E.g. Milvus, Pinecone, Chroma, or similar) 

• Strong knowledge of prompt engineering, context engineering and principles of LLM evaluation 

Production Systems and DevOps Practices 

• A strong understanding of secure coding practices and application observability (monitoring, logging & tracing) 

• Proficiency with application containerization and version control systems 

• Hands-on experience of building/maintaining MLOps and CI/CD pipelines using Internal Developer Platform (IDP) 

• Proven experience of deploying applications on cloud platforms (AWS, GCP, or Azure etc.) 

Bonus Skills 

• Understanding of workflows in data backup and recovery products 

• Familiarity with LLM fine-tuning techniques (e.g. LoRA, PEFT) 

• Experience with container orchestration (e.g. Kubernetes)