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We're building a declarative layer for financial research. Think of it like Vercel for financial research - just as Vercel lets you spin up a new project with vercel init and handles all the infrastructure behind the scenes, we want to be able to declare an array of financial research processes and have the system handle orchestration, execution, and delivery. The goal is to make spawning new research representations as frictionless as starting a new Vercel project - define what you want, and the platform takes care of the rest.
Requirements
- Expert-level Python proficiency, as it is a primary language for all development.
- Deep technical knowledge of relational databases (PostgreSQL), including schema normalization, writing complex joins, query optimization, and managing indexing for high-concurrency environments.
- Proficiency with NoSQL Databases, with a deep understanding of when to use document, key-value, or vector stores to handle unstructured LLM outputs and high-velocity research data.
- Comprehensive knowledge of deployment approaches, including experience with CI/CD pipelines, containerization (Docker/Kubernetes), and different deployment strategies.
- Multi-platform deployment experience, with the ability to navigate and deploy across various environments ranging from serverless to traditional cloud providers (AWS, GCP, or Azure).
- Proven experience with serverless compute (e.g., Modal) and cloud-native architectures.
- Hands-on experience with LLM APIs including direct integration with OpenAI, Anthropic, xAI, or Google.
- Familiarity with AI orchestration frameworks such as PydanticAI.
- High level of resourcefulness and the ability to quickly master new concepts as the AI landscape evolves
- Experience working with financial data providers like S&P Global, FactSet, or SEC Edgar
- Familiarity with modern AI tooling APIs such as Exa or Parallel
- Write clean, maintainable Python code to build out the core orchestration engine and API layers
- Develop and debug durable execution logic, implementing state management, automated retries, and cost-control triggers for long-running tasks
- Build and maintain integrations for LLM providers and financial data APIs, ensuring high availability and low latency
- Design and implement database schemas in PostgreSQL and NoSQL stores, writing optimized queries and managing migrations
- Create unified API abstractions that allow the system to switch between different LLM models and storage backends via configuration
- Build automated test suites and evaluation pipelines to validate the accuracy of LLM outputs and system performance
- Configure and automate deployment pipelines across multiple platforms, including CI/CD orchestration and container management
- Build and manage scalable infrastructure using serverless compute (Modal) and cloud-native services to ensure high availability
- Awesome projects with an impact
- Udemy courses of your choice
- Team-buildings, events, marathons & charity activities to connect and recharge
- Workshops, trainings, expert knowledge-sharing that keep you growing
- Clear career path
- Absence days for work-life balance
- Flexible hours & work setup - work from anywhere and organize your day your way
Key Skills
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