Principal Data Scientist

• Design, develop, and maintain AI-powered applications and services using LLMs and generative AI technologies.
• Build and enhance Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, chunking, embeddings, retrieval, reranking, context management, and response generation.
• Integrate LLMs, vector databases, APIs, and other AI services into scalable software applications.
• Develop and optimize prompts, retrieval strategies, evaluation approaches, and AI workflows to improve accuracy and relevance.
• Build production-quality software with a focus on scalability, reliability, performance, security, and maintainability.
• Design and develop REST APIs, microservices, and other backend services supporting AI applications.
• Work with structured and unstructured data and integrate data sources into AI/ML applications.
• Evaluate LLM and RAG performance using appropriate metrics, testing strategies, and evaluation frameworks.
• Troubleshoot and optimize AI applications across development, testing, and production environments.
• Collaborate with software engineers, data scientists, product teams, and other stakeholders to deliver AI solutions.
• Stay current with emerging LLM, RAG, agentic AI, and generative AI technologies and identify opportunities to apply them to business problems., Planning Research Debugging LangChain Operations Automation Kubernetes LlamaIndex Agentic AI Scalability Core Product Data Science Communication Observability Deep Learning AWS SageMaker Hallucinations Problem Solving Semantic Search Knowledge Graph Legal Citations Language Models Machine Learning BERT (NLP Model) Enterprise Search Business Valuation Prompt Engineering Workflow Management Amazon Web Services Product Engineering Multi-Agent Systems Knowledge Management Full Stack Development Reinforcement Learning Knowledge Distillation Artificial Intelligence Large Language Modeling Business Transformation Business Risk Management Machine Learning Algorithms Software Release Life Cycle Hugging Face (NLP Framework) Python (Programming Language) Artificial Intelligence Strategy Generative Artificial Intelligence PyTorch (Machine Learning Library) Transformer (Machine Learning Model) Artificial Intelligence Infrastructure Application Programming Interface (API) +0 AI Engineer CareerCircle

Remote

Chunking Debugging TypeScript Algorithms Agentic AI Scalability Reliability RESTful API Microservices Systems Design Data Retrieval Problem Solving Data Structures Maintainability Vector Database Machine Learning Analytical Skills Unstructured Data Context Management Workflow Management Development Testing Software Engineering Software Development Artificial Intelligence Large Language Modeling Application Development C# (Programming Language) Go (Programming Language) Java (Programming Language) Python (Programming Language) Retrieval Augmented Generation Troubleshooting (Problem Solving) JavaScript (Programming Language) Object-Oriented Programming (OOP) Generative Artificial Intelligence Application Programming Interface (API) Applications Of Artificial Intelligence +0

Debugging TypeScript Algorithms Agentic AI Scalability Reliability RESTful API Microservices Systems Design Data Retrieval Problem Solving Data Structures Maintainability Vector Database Machine Learning Analytical Skills Unstructured Data Context Management Workflow Management Development Testing Software Engineering Software Development Artificial Intelligence Large Language Modeling Application Development C# (Programming Language) Go (Programming Language) Java (Programming Language) Python (Programming Language) Retrieval Augmented Generation Troubleshooting (Problem Solving) JavaScript (Programming Language) Object-Oriented Programming (OOP) Generative Artificial Intelligence Application Programming Interface (API) Applications Of Artificial Intelligence, We are looking for an experienced AI Engineer with a strong software engineering background to design, develop, and enhance AI-powered applications and services. The ideal candidate has hands-on experience building Retrieval-Augmented Generation (RAG) solutions and working with Large Language Models (LLMs), while also having strong fundamentals in software engineering, system design, APIs, and scalable application development.

This role is language-agnostic. Candidates with strong experience in Python, Java, JavaScript/TypeScript, C#, Go, or another modern programming language are encouraged to apply., * 5+ years of professional software engineering or application development experience.

• Hands-on experience building and implementing Retrieval-Augmented Generation (RAG) solutions.
• Hands-on experience working with Large Language Models (LLMs) and generative AI applications.
• Strong software engineering fundamentals, including object-oriented programming, data structures, algorithms, APIs, and system design.
• Strong experience with at least one modern programming language such as Python, Java, JavaScript/TypeScript, C#, Go, or similar.
• Experience developing production-quality applications, services, or APIs.
• Experience working with databases and/or data retrieval systems.
• Experience with cloud platforms and modern software development practices.
• Strong debugging, problem-solving, and analytical skills.