About the Role We are building an AI-powered financial research platform focused on real-time insights from SEC filings, market data, and sector intelligence across mining, industrials, and beyond. Our platform combines large-scale data pipelines, search infrastructure, and LLM-driven workflows to power an AI stock research assistant, internal analytics systems, and investor-facing tools. We’re looking for a strong engineer who can own systems end-to-end from data ingestion to APIs to production deployment and help scale a live platform. You’ll work directly with a high-impact team, with real ownership and the ability to influence technical direction. What You’ll Do Build and scale an AI-powered stock research assistant that processes SEC filings and financial data in real time Design and maintain data pipelines for ingesting and transforming large-scale financial datasets (EDGAR, market data, etc.) Develop backend systems and APIs powering search, analytics, and AI workflows Implement and optimize semantic search systems using embeddings and vector databases Build internal tools and dashboards for analytics, content performance, and investor insights Improve performance, reliability, and scalability across production systems Take ownership of features from design to implementation, deployment, monitoring. Required Skills Strong backend experience with Python (FastAPI or similar) Solid knowledge of SQL (Postgres/MySQL) and data modeling Experience building and maintaining production-grade APIs Hands-on experience with AWS (EC2, RDS, or similar services) Experience with data pipelines / ETL systems Good understanding of system design and scalable architectures Familiarity with vector databases (pgvector, Pinecone, Weaviate, etc.) Experience with LLM-based systems or AI applications Knowledge of Docker, CI/CD, or cloud deployments Nice to Have Exposure to financial data / SEC filings (EDGAR), metals and mining data Experience building analytics dashboards or internal tools What We Look For Strong ownership mindset Ability to debug and solve problems independently Clean, maintainable, production-quality code Comfort working in a fast-moving, unstructured environment Clear communication in a remote team