🕒 6 days ago
Build and evolve Mercury Command, an LLM-powered financial assistant, by designing and shipping new capabilities, defining how they should work with product and compliance teams, and testing them.
Founding Engineer
🕒 yesterday
PythonFastapiTypeScriptReact
📜 Description
- Build and ship features across frontend, backend, and real-time systems.
- Create data pipelines and internal tools to add sources and maintain industry coverage reliably.
- Improve AI agent parsing and extraction by balancing agent reasoning with deterministic software.
- Own work end to end, from data inspection and quality assurance to instrumentation, production releases, and ongoing fixes.
- Develop a company ontology and an initial earnings research product.
🛠️ Requirements
- At least 2 years of experience building, shipping, and operating production systems, with approximately 7 or fewer years of professional experience.
- Hands-on experience building and deploying agentic AI systems or LLM-based applications in production.
- Full-stack capability, including Python with FastAPI or an equivalent framework, TypeScript, React, backend systems, and data pipelines.
- Experience with ETL, data modeling, SQL, relational database design and optimization, and production observability and debugging.
- Experience with AWS, deployment, and real-time or streaming data systems.
- Strong ownership and production judgment, with depth in backend engineering, data infrastructure, applied AI, or product engineering.
- Capital markets, financial research, investment banking, or broader financial services experience is a plus. Familiarity with modern data tools, edge infrastructure, or AI/ML tooling is also helpful.
- Must be a US citizen and able to work on-site in New York City.
✨ Benefits
- Base salary: $156,000 to $182,000 annually. Visa sponsorship is not available.
Full job description
About the Role
Join a small, early-stage team building AI-powered research tools for professional investors, initially focused on healthcare. As a founding engineer, you will develop the infrastructure and product systems that help AI agents turn diverse data sources into reliable, continuously updated industry models.
What You'll Do
Build and ship product features across frontend, backend, and real-time systems.
Create data pipelines and internal tools that make it faster and more reliable to add sources and maintain industry coverage.
Improve AI agent parsing and extraction systems, balancing agent reasoning with deterministic software.
Own work end to end, including data inspection, quality assurance, instrumentation, production releases, and ongoing fixes.
Develop a company ontology and an initial earnings research product.
What We're Looking For
At least 2 years of experience building, shipping, and operating production systems, with approximately 7 or fewer years of professional experience.
Hands-on experience building and deploying agentic AI systems or LLM-based applications in production.
Full-stack capability, including Python with FastAPI or an equivalent framework, TypeScript, React, backend systems, and data pipelines.
Experience with ETL, data modeling, SQL, relational database design and optimization, and production observability and debugging.
Experience with AWS, deployment, and real-time or streaming data systems.
Strong ownership and production judgment, with depth in backend engineering, data infrastructure, applied AI, or product engineering.
Capital markets, financial research, investment banking, or broader financial services experience is a plus. Familiarity with modern data tools, edge infrastructure, or AI/ML tooling is also helpful.
Must be a US citizen and able to work on-site in New York City.
Compensation & Benefits
Base salary: $156,000 to $182,000 annually. Visa sponsorship is not available.
Location
On-site in New York City, New York.
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