AI Infrastructure Platform Engineer (Python)

Job Summary

We are building the foundational platform that powers next-generation AI agents and intelligent systems at scale. This is not a model research or prompt engineering role. The focus is on designing and building highly scalable, reliable backend systems that enable agent-driven applications to operate in production environments.

Duties and Responsibilities

• Design and build scalable backend services in Python for AI and agent platforms
• Architect systems that handle high concurrency, large volumes of data, and low-latency requirements
• Build and operate microservices deployed on Kubernetes
• Design systems with reliability, fault tolerance, and observability as core principles
• Plan for horizontal scalability to support rapid growth and increasing usage
• Work on asynchronous processing, distributed workflows, and event-driven architectures
• Collaborate with cross-functional teams to define platform capabilities that support AI use cases
• Continuously improve system performance, reliability, and cost efficiency

Requirements and Qualifications

• Strong proficiency in Python with experience building production-grade systems
• Solid understanding of data structures, algorithms, and core computer science fundamentals
• Experience designing and building distributed systems at scale
• Hands-on experience with concurrency, multithreading, or asynchronous programming
• Experience with microservices architecture and API design
• Practical experience with Kubernetes and containerized deployments
• Ability to design systems that account for failure scenarios, scaling challenges, and performance trade-offs

Preferred Qualifications

• Experience with AWS or similar cloud platforms
• Familiarity with event-driven systems such as Kafka or pub/sub architectures
• Experience with caching strategies such as Redis
• Exposure to observability tools for logging, monitoring, and tracing
• Some familiarity with AI or ML systems, LLMs, or agent-based architectures