Build and scale an AI-powered stock research platform: design data pipelines ingesting SEC and market data, develop backend APIs, implement semantic search with embeddings and vector DBs, improve production reliability and performance, and own features end-to-end from design through deployment and monitoring.
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
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