3+ years in distributed systems or high-availability backends, preferably in fast-paced environments
Strong proficiency in Python and at least one systems programming language (e.g., Go, Rust, C++)
Experience with cloud platforms and container orchestration (AWS/GCP/Azure, Docker, Kubernetes)
Proficient in database management and optimization (SQL/NoSQL)
Focus on code quality, correctness, and performance
Ability to use advanced AI coding tools to enhance productivity while ensuring code quality
Responsibilities
Design and implement scalable backend services and APIs
Build infrastructure for AI/ML workflows with high throughput and low latency
Setup and manage databases, including schema design and performance tuning
Optimize performance, reliability, and security across all layers
Implement observability practices for monitoring and performance tuning
Collaborate with research and infrastructure teams to support experimental efforts
Contribute to engineering culture through mentorship and code reviews
Benefits
Opportunity to work on impactful AI projects in financial settings
Join an elite, small team with a high degree of autonomy
Collaborate with founders and ex-researchers from prestigious companies
Experience a work environment free from bureaucracy
Engage in cutting-edge research and technologies
Full Job Description
About the Role You'll architect, build, and maintain the distributed systems, APIs, and backend infrastructure that power world-class AI research and deployment. Your work will enable rapid experimentation, robust data flows, and scalable compute. This is a hands-on role for someone who thrives in small, high-agency teams.
Responsibilities
Design and implement scalable backend services, data pipelines, and APIs
Build infrastructure for high-throughput, low-latency AI/ML workflows
Set up and manage databases (SQL/NoSQL), including schema design, replication, indexing, and performance optimization
Optimize for performance, reliability, and security at every layer
Implement observability best practices (logging, tracing, monitoring, performance tuning)
Work closely with research and infra teams to support experimental velocity
Contribute to core engineering culture, including code reviews and mentorship
Requirements
3+ years building distributed systems or high-availability backends (preferably in fast-moving or high-stakes environments)
Strong proficiency in Python and at least one systems language (e.g., Go, Rust, C++)
Experience with cloud platforms, containerization, and orchestration (AWS/GCP/Azure, Docker, Kubernetes)
Database setup, management, and optimization experience (SQL/NoSQL)
Relentless focus on code quality, correctness, and performance
Comfortable leveraging modern AI coding tools (Cursor, Claude Code, Codex, etc.) to increase productivity & code output while maintaining high code quality, maintainability, and structure
Bonus - Agentic workflows / applied AI integration
Experience supporting or integrating agentic AI workflows into backend systems (e.g., LangChain, LangGraph, Semantic Kernel, Haystack, or custom frameworks)
Familiarity with persistence/checkpointing, streaming pipelines, and vector/knowledge store integrations
