AI/ML DATA ENGINNER

Role- AI/ML DATA ENGINNER – HIGHLY EXPERIENCED ON SQL CODING, DATABRICKS AND SNOWFLAKES Location - Santa Clara CA(Onsite) Type: Contract Job Summary We are looking for an experienced AI Data Application Engineer to build and deploy AI-driven solutions that solve real business problems. This role bridges AI/ML capabilities with production-ready systems and works closely with product, data science, and platform teams. Key Responsibilities Build AI-powered applications using machine learning and generative AI • Integrate ML models, LLMs, and AI services into applications • Develop APIs and microservices for AI solutions • Work with data scientists to deploy models into production • Implement prompt engineering and inference pipelines • Ensure performance, scalability, security, and reliability • Support real-time and batch AI use cases • Set up monitoring for application and AI behavior • Manage model versioning, A/B testing, and rollback • Ensure data privacy and responsible AI compliance • Contribute to architecture and best practices • Troubleshoot production issues • Mentor junior team members Required Skills & Qualifications Application Development 5–6 years of software development experience • Strong skills in Python or JavaScript/TypeScript • Experience with FastAPI, Flask, Django, or Node.js • Good understanding of APIs, microservices, and system design • Frontend experience (React, Angular, Vue) is a plus AI & Machine Learning Experience integrating ML and AI services into applications • Understanding of ML lifecycle and inference • Experience with LLMs (OpenAI, Azure OpenAI, AWS Bedrock, Hugging Face) • Knowledge of prompt engineering and RAG • Familiarity with embeddings and vector search Data & Backend Strong SQL and database experience (relational and NoSQL) • Experience with Snowflake and Databricks platforms • Experience with data pipelines and analytics systems • Knowledge of APIs, caching, and messaging systems (Kafka, RabbitMQ) Cloud & DevOps Experience with AWS, Azure, or GCP • Hands-on with Docker and Kubernetes • Familiarity with CI/CD pipelines • Exposure to cloud-native AI services is a plus