Data Scientist: AI/ML Engineer

Introduction
We are seeking an experienced Data Scientist- AI Engineer with a strong background in Generative AI and AI agents to join our Asset Engineering team. The ideal candidate will have expertise in RAG Agentic Workflows and Large Language Models (LLMs) and a passion for building innovative AI solutions.
As an AI Engineer you will be responsible for designing developing and deploying AI-powered applications that integrate with our existing software AI framework and infrastructure based on Watsonx IBM Sales Cloud (Powered by Salesforce) and IBM Consulting Advantage Assistants.

Your Role and Responsibilities

• Design develop and deploy AI agentic applications by leveraging LLMs prompt engineering and Retrieval Augmented Generation (RAG) within agent workflow frameworks
• Collaborate with cross-functional teams to identify and prioritize project requirements
• Integrate AI models with Salesforce Watsonx Assistant Watsonx Orchestrate Slack and other web applications using RESTful APIs and web frameworks such as Spring Boot or Flask/FastAPI.
• Develop and maintain relational and vector databases such as PostgreSQL and Milvus
• Stay up to date with the latest advancements in AI and machine learning and apply this knowledge to improve our AI applications

Required Technical and Professional Expertise

• Proficiency in Prompt Engineering LLMs Retrieval Augmented Generation and Python programming
• Experience with GitHub software development CICD cloud and deployment database management systems such as MySQL or PostgreSQL vector database (Milvus Weaviate) and graph database (Neo4j)
• Experience using LLMs in software applications including prompting calling and processing outputs
• Experience with AI frameworks such as LangChain Llamma Index Crew.ai Autogen watsonx.ai and the models available in the platform
• Experience with LLM applications such as ChatGPT Perplexity RAG frameworks or engines (RAGflow Haystack)

Preferred Technical and Professional Expertise

• Experience in designing and implementing large-scale AI solutions including data ingestion storage processing and deployment.
• Experience working on LLMs Model Training & Evaluation Performance Benchmarking.
• Experience in developing multi-agent applications using frameworks like Crew AI AutoGen etc