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Full-Stack Lead - GenAI & LLM Applications

Negotiable Salary

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California, USA

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Job Opening: Full-Stack Lead – GenAI & LLM Applications Location: South San Francisco (SSF) - Hybrid - 3 days onsite Start Date: Immediate About the Role We are seeking a hands-on Full-Stack Developer with Generative AI expertise to join our team and lead the development of a real-time AI application leveraging AWS serverless architecture, FastAPI, and LLM-based pipelines. The ideal candidate is a builder with a deep understanding of full-stack development, cloud-native applications, and AI-powered user experiences.   Your Responsibilities ● Build and enhance React-based frontends hosted on CloudFront ● Design scalable, low-latency APIs using FastAPI (Python) integrated with API Gateway (REST + WebSocket) ● Develop AWS Lambda functions for backend services, data handling, and orchestration ● Hands-on experience with OpenSearch for implementing scalable search functionality ● Manage authentication using SSO, and enable secure access flows ● Integrate real-time WebSocket interfaces for LLM streaming and dashboarding ● Work closely with data science teams to connect LLM pipelines (LangChain + RAG) and vector search mechanisms ● Design and maintain serverless data layers using DynamoDB, Aurora PostgreSQL, Athena, and S3 ● Participate in CI/CD automation using GitHub Actions, CloudFormation/CDK, and manage IAM roles/policies ● Collaborate on data pipelines using AWS Glue, Airflow (MWAA), and Sagemaker for model training/inference   Key Technologies ● Frontend: React, TypeScript, CloudFront ● Backend: FastAPI (Python), AWS Lambda, API Gateway (REST + WebSocket), Cognito ● Search & Storage: OpenSearch, DynamoDB, Aurora PostgreSQL, S3, Athena ● GenAI & RAG: LangChain, FAISS, Pinecone, OpenAI, Claude, AWS Bedrock ● Data Engineering: AWS Glue, Airflow (MWAA) ● DevOps: GitHub Actions, CloudFormation/CDK, IAM Roles ● Streaming & Realtime: WebSockets, LLM streaming pipelines   You Should Have ● Proven experience in building production-grade GenAI features using LLM APIs and RAG pipelines ● Hands-on experience with serverless app development on AWS ● Solid understanding of FastAPI, microservices architecture, and REST/WebSocket API design ● Comfort with both structured data (PostgreSQL) and NoSQL (DynamoDB) ● Experience working in a CI/CD DevOps environment with infrastructure-as-code ● Excellent problem-solving skills, and ability to troubleshoot complex cloud-native systems

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