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
