Senior Backend Engineer (Python / AI Platform)
Location: Remote
Experience: 6–10 years
About Rapid Alpha
Rapid Alpha is building EVOS, a platform designed to make AI usable for serious business decisions.
General-purpose LLM tools are powerful but unreliable. EVOS solves this by combining curated datasets, structured taxonomies, and AI workflows to produce evidence-based intelligence on technologies, markets, and companies.
The platform integrates:
- structured knowledge graphs
- document ingestion pipelines
- AI-assisted analysis workflows
- scalable SaaS infrastructure
Our long-term vision is for EVOS to become:
- the marketplace for curated datasets from domain experts
- the marketplace for reusable prompts and AI workflows
- the operating system for strategic decision-making
The Role
We are looking for a Senior Backend Engineer (Python) to help architect and scale the EVOS platform.
This role is ideal for a backend engineer who enjoys building data-heavy, AI-enabled SaaS systems and wants to work close to product architecture.
You will primarily work in Python services and cloud infrastructure, while collaborating with the frontend team building the platform interface in React.
This is not a ticket-driven development role. You will help shape the architecture of a system that integrates data ingestion, AI pipelines, and interactive applications.
What You’ll Build
You will contribute to the core infrastructure behind the EVOS platform:
Backend Services
- Build and scale backend services in Python (Flask / FastAPI)
- Design and maintain REST APIs powering the platform
- Implement async processing pipelines for AI workloads
- Build systems for document ingestion, classification, and analysis
Data & AI Workflows
- Integrate LLM and AI services into product workflows
- Build data pipelines supporting NLP, embeddings, and semantic search
- Work with structured datasets that power technology and market intelligence
Infrastructure & Scaling
- Design systems that handle concurrent workloads and background processing
- Implement queue-based architectures for batch workloads
- Optimize performance across PostgreSQL, Redis, and AWS infrastructure
Platform Architecture
- Help shape a scalable SaaS architecture
- Ensure AI workloads do not disrupt application stability
- Improve system reliability and observability
Technology Stack
Core stack:
Backend
- Python (Flask / FastAPI)
- REST APIs
- asynchronous processing
Frontend
- React
- JavaScript
Infrastructure
- AWS (EC2, S3, RDS)
- containerized workloads
Data
- PostgreSQL
- Redis / queue systems
AI
- OpenAI / LLM APIs
- NLP workflows
- embeddings / vector search (preferred)
What We’re Looking For
Core Engineering Skills
- 6–10 years of backend or full-stack engineering experience
- Strong backend development in Python
- Experience designing scalable APIs and backend services
- Experience working with PostgreSQL in production environments
Systems & Architecture
Experience building or operating systems involving:
- background job processing
- asynchronous workloads
- distributed services
- scalable SaaS platforms
Cloud Infrastructure
Experience deploying production systems on:
- AWS
- containerized workloads
- CI/CD pipelines
Frontend Familiarity
Comfort collaborating with frontend teams using:
- React
- modern JavaScript
You do not need to be a frontend specialist but should be comfortable working in a full-stack environment.
- building AI-enabled applications
- integrating OpenAI or similar LLM APIs
- working with NLP pipelines
- designing queue-based architectures
- experience with data pipelines or document ingestion systems
What Makes This Role Unique
This is not just another SaaS fullstack job.
You will help build a platform that:
- structures global technology intelligence
- integrates AI into decision-making workflows
- enables companies to analyze markets and innovation systems
The platform combines knowledge graphs, AI workflows, and scalable cloud infrastructure to power evidence-based strategic analysis.
Why Join Rapid Alpha
- 11-Month Work Year
Rapid Alpha operates on an intentional schedule that includes two company-wide recharge breaks each year (July and late December), plus federal holidays and additional PTO. - Work on a platform at the intersection of AI, data, and strategy
- High ownership and architectural influence
- Build systems used by leaders making high-stakes decisions
- Remote-first environment with flexible work structure