This Is a True 0→1 Engineering Opportunity
You'll be one of the earliest technical leaders helping define how the platform is built. The architecture, engineering culture, technical standards, and many of the core technical decisions still lie ahead.
AI Isn't a Feature—It's the Product
This company is building an AI-native platform powered by LLMs, agent-based systems, retrieval-augmented generation (RAG), and modern machine learning infrastructure. You'll design the systems that orchestrate intelligent agents, production AI workflows, and large-scale data pipelines.
You'll Wear Multiple Hats
- Designing platform architecture
- Building production services
- Shipping AI features
- Improving cloud infrastructure
- Working with product on roadmap decisions
- Partnering with data scientists to productionize new models
What You'll Do
- Design and build the company's AI-first platform architecture.
- Develop agent-based systems, orchestration layers, and inference pipelines.
- Build scalable data ingestion, transformation, and feature engineering pipelines.
- Partner with Data Science to productionize machine learning models and AI systems.
- Own engineering execution from planning through deployment.
- Design reliable cloud infrastructure, APIs, and backend services.
- Establish engineering best practices, testing standards, and CI/CD processes.
- Ensure platform reliability, scalability, observability, and security.
Tech Stack
- Python
- AWS
- Terraform
- PostgreSQL
- Event-driven architecture (SNS/SQS)
- Microservices
- SvelteKit
- LLMs & Generative AI
- Retrieval-Augmented Generation (RAG)
- Agentic AI Systems
We're Looking For Someone Who...
- Has 6–10+ years of software engineering experience.
- Has built production AI or machine learning systems.
- Has deep experience with Python and cloud-native architectures.
- Has worked with LLMs, RAG pipelines, or agent-based systems.
- Has startup experience and enjoys building in ambiguous environments.
- Writes clean, maintainable, production-quality code.