GenAI Engineer

Responsibilities

• GenAI use cases requirements understanding working with product owners, business and design LLM solutions aligned with client's approved RAG patterns.
• Drive data requirements conversations and work with data office to get required data for the use case.
• Design efficient chunking & indexing strategies to support answer generation as per expectations.
• Develop and deploy inference APIs using frameworks like langchain and deploy to AKS or function apps.
• Capable to pick up UI work as needed to support front end integration collaborating with UI team.
• Support GenAI knowledge BOTs in production by monitoring user feedback and improve BOT response quality through enhancements as per feedback.
• Embrace best practices, processes related to MLOps, Coding best practices.
• Collaborate with existing members in the team, contribute to reusable GenAI code base. 

Required

• Minimum of 5 years of experience solving high-impact business problems using Machine learning & latest advancements in LLMs.
• Proven experience as a ML Engineer, with a strong focus on generative AI, prompt engineering, and RAG applications.
• Hands-on experience using Azure AI search, Langchain, other Vector stores.
• Experience in Azure OpenAI. Open-source LLMs is a plus.
• Strong software development skills with proficiency in Python, Pyspark, preferably using Databricks Azure ML.
• Basic knowledge of React or equivalent UI frameworks is a plus.
• Strong experience in supporting production applications post development and continuously improve response quality to increase benefits.
• Experience in productionizing code through the DevOps pipeline (git, Jenkins pipeline, code scan).