Your Role as AI Software Engineer
What makes this role stand out:
- You have a background in backend development and system architecture, and you feel confident working in the cloud.
- You design and build scalable, complex microservices-based systems that integrate AI models.
- You understand the limitations and challenges of GenAI systems from inference costs to latency and security.
Why it’s worth it:
- Here, you’re not “just a backend developer,” you have the chance to build the next generation of AI-powered applications.
- Projects often require bridging traditional systems with GenAI/LLMs, giving you real influence over architecture.
- Close collaboration with MLEs and Data Scientists gives you exposure to the full AI stack from models to APIs and integrations.
A few project examples:
- Training multimodal LLMs for drug discovery.
- Building AI voicebots that double conversion rates.
- Creating a GenAI solution for a leading US legal company together with the OpenAI team.
- Running GenAI on edge devices with cloud-level performance.
All of this in a setup that feels like an AI-driven software house: remote-first, flexible, and packed with specialists who are open to sharing knowledge and experimenting with the newest tech.
The ideal candidate:
- Has 5+ years of experience in software engineering with strong proficiency in Python.
- Understands microservices and event-driven architectures, and can build scalable APIs and microservices (FastAPI, Flask, Django).
- Is experienced with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
- Has worked with both SQL and NoSQL databases, as well as data pipeline integration.
- Follows best engineering practices: CI/CD, automated testing, version control.
- Is passionate about building AI-driven applications and integrating Generative AI and LLMs into production systems, with a focus on scalability, latency, inference cost optimization, including integration via MCP.
- Communicates clearly and effectively, collaborating with ML Engineers, Data Scientists, and clients.
- Bonus points for experience with vector databases, streaming systems, or MLOps.