Principal Member of technical Staff- AI & Data Engineering

Role Overview: Join a dynamic team working towards creating a thriving ecosystem that delivers accessible, high-quality, and sustainable healthcare for all. As a Principal Member of Technical Staff (PMTS), your expertise in designing, developing, debugging, and maintaining AI-powered applications and data engineering workflows for both local and cloud environments will be crucial. You will be involved in large-scale projects, optimizing AI/ML pipelines, and ensuring scalable data infrastructure. Key Responsibilities: - Develop AI-driven applications, microservices, and automation workflows using FastAPI, Flask, or Django, ensuring cloud-native deployment and performance optimization. - Integrate OpenAI APIs (GPT models, Embeddings, Function Calling) and Retrieval-Augmented Generation (RAG) techniques to enhance AI-powered document retrieval, classification, and decision-making. - Design, build, and optimize scalable data pipelines for AI/ML workflows using Pandas, PySpark, and Dask, integrating data sources such as Kafka, AWS S3, Azure Data Lake, and Snowflake. - Enhance AI model inference efficiency by implementing vector retrieval using FAISS, Pinecone, or ChromaDB, and optimize API latency with tuning techniques (temperature, top-k sampling, max tokens settings). - Develop scalable RESTful APIs for AI models and data services, ensuring integration with internal and external systems while securing API endpoints using OAuth, JWT, and API Key Authentication. - Collaborate with cross-functional teams including AI/ML, Data Engineering, DevOps, Product, UX, and Compliance to deliver impactful solutions that enhance products and services. - Mentor junior engineers on AI model integration, API development, and scalable data engineering best practices, and conduct knowledge-sharing sessions. Qualifications Required: - 12-18 years of experience in software engineering or AI/ML development, preferably in AI-driven solutions. - Hands-on experience with Agile development, SDLC, CI/CD pipelines, and AI model deployment lifecycles. - Bachelor's Degree or equivalent in Computer Science, Engineering, Data Science, or a related field. - Proficiency in full-stack development with expertise in Python (preferred for AI), Java. - Experience with structured & unstructured data: SQL (PostgreSQL, MySQL, SQL Server), NoSQL (OpenSearch, Redis, Elasticsearch), Vector Databases (FAISS, Pinecone, ChromaDB). - Proficiency in cloud and AI infrastructure including AWS (Lambda, SageMaker, ECS, S3), Azure (Azure OpenAI, ML Studio), and GenAI Frameworks & Tools (OpenAI API, Hugging Face Transformers, LangChain, LlamaIndex, AutoGPT, CrewAI). - Experience in LLM deployment, retrieval-augmented generation (RAG), AI model evaluation, and responsible AI deployment. - Strong problem-solving skills, AI ethics awareness, and the ability to collaborate across AI, DevOps, and data engineering teams.,