AWSBigQueryCloudETLFlaskGoogle Cloud PlatformJavaScriptNext.jsPandasPythonReactSQLAIOpenAIAnthropicRAGLangChainLlamaIndexLangGraphPineconeWeaviateData EngineeringAnalyticsReact.jsFastAPIGCPGoogle CloudCloud RunCloud FunctionsVertex AIGitVersion ControlRemote Work
About this role
Role Overview
Build internal tools, connectors, and AI agents that automate critical Media and Operations workflows;
Design RAG (Retrieval-Augmented Generation) systems and automations ensuring data security and privacy;
Rapidly convert business pain points into testable interfaces to validate value before scaling;
Connect siloed tools via APIs to create unified workflows;
Act as a technical reference, demonstrating that complex problems can be solved with software and AI.
Requirements
Solid Software Engineering: Proficiency in Python (backend and data focus), version control best practices (Git), and independence in debugging;
LLMs and Frameworks Fluency: Practical experience integrating APIs (OpenAI, Vertex AI, Anthropic) and using orchestration frameworks like LangChain, LangGraph, or LlamaIndex;
Full Stack Web Development: Ability to build robust REST APIs (FastAPI/Flask) and functional interfaces for MVPs (Streamlit or basic React);
Applied Data Engineering: Skill with Pandas, SQL (BigQuery), and building lightweight ETL pipelines to feed AIs;
Cloud & Deployment: Experience deploying projects to production using GCP (Cloud Functions, Cloud Run) or AWS;
Agent Architecture: Ability to design flows where AI performs actions (Tool Calling) and not just converses;
Google Apps Script: Skill to automate the Google Workspace ecosystem natively (Sheets, Slides);
Modern Front-end: Knowledge of React.js or Next.js for polishing internal tools;