AI Engineer (Only on W2)

Job Role: AI Engineer (Only on W2) Location: Hybrid - Austin, TX Position Type: Contract About the Role We are seeking a highly skilled AI Engineer with strong expertise in Retrieval-Augmented Generation (RAG), Java/React front-end development, and database technologies (MongoDB & PL/SQL). The ideal candidate will bridge the gap between AI-driven backend solutions and enterprise applications, ensuring scalability, performance, and seamless integration of AI into business processes. Key Responsibilities • Design, develop, and implement RAG (Retrieval-Augmented Generation) pipelines for intelligent data retrieval and generative AI applications. • Build and maintain microservices and APIs using Java/Spring Boot for scalable AI solutions. • Develop front-end components in React.js to deliver responsive, user-friendly AI applications. • Work with MongoDB for NoSQL data storage and optimize performance for AI-driven applications. • Design and maintain PL/SQL procedures, triggers, and queries for relational data processing and integration with AI pipelines. • Collaborate with Data Scientists, ML Engineers, and Business Analysts to operationalize AI/ML models into production. • Ensure data security, governance, and compliance when integrating AI with structured/unstructured data sources. • Troubleshoot, optimize, and maintain AI systems to ensure high availability and low latency. • Stay updated with advancements in Generative AI, RAG, LLMs (e.g., GPT, LLaMA, Falcon), and AI orchestration frameworks. Required Skills & Qualifications • Strong expertise in Retrieval-Augmented Generation (RAG) concepts, including: • Vector databases (e.g., Pinecone, Weaviate, FAISS, or MongoDB Atlas Vector Search). • Prompt engineering and fine-tuning large language models (LLMs). • Document embedding, semantic search, and context injection techniques. • Proficiency in Java (Spring Boot, REST APIs, microservices). • Front-end development with React.js (hooks, state management, component design). • Strong experience with MongoDB (data modelling, aggregation, indexing, and performance tuning). • Hands-on experience with PL/SQL (procedures, functions, triggers, complex queries). • Familiarity with cloud platforms (AWS / Azure / GCP) and containerization (Docker, Kubernetes). • Experience in integrating AI APIs (OpenAI, Hugging Face, Lang Chain, etc.). • Solid understanding of software development best practices: CI/CD, version control (Git), testing. • Excellent problem-solving, communication, and collaboration skills. Nice-to-Have Skills • Exposure to GraphQL APIs. • Knowledge of Kafka / event-driven architecture. • Experience with MLOps tools (MLflow, Kubeflow, Vertex AI, SageMaker). • Familiarity with Data Lakes / Data Warehouses. Education & Experience • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Engineering, or related field. • 5–10 years of experience in software engineering, with at least 2+ years in AI/LLM-based projects.