Software Development Engineer II (SDE-2)

The Role

Were looking for an SDE-2 with a strong foundation in distributed systems and backend engineering to help scale our core AI infrastructure. You will own critical services, make high-impact architectural decisions, and optimize systems that serve millions of requests.

This role is ideal for someone who thrives on complexity, enjoys debugging systems at scale, and can balance development velocity with long-term system reliability and health.

What You'll Do

• Design & Build Scalable Systems: Architect and implement high-performance backend services and distributed systems that power our AI platform.
• Own Critical Components: Take end-to-end ownership of key microservicesfrom design and development to deployment, monitoring, and on-call support.
• Optimize for Performance: Identify and resolve bottlenecks related to latency, throughput, scalability, and resource utilization, delivering measurable improvements.
• Make Sound Technical Decisions: Evaluate trade-offs between consistency, availability, and partition tolerance, and choose appropriate technologies, patterns, and architectures.
• Collaborate Cross-Functionally: Work closely with ML engineers, product managers, and infrastructure teams to deliver reliable, production-grade systems.
• Mentor & Elevate: Guide junior engineers through code reviews, design discussions, and technical mentorship.

What We're Looking For

Must-Have Skills

• 4+ years of professional software engineering experience, primarily in backend development.
• Strong proficiency in at least one modern backend programming language, such as Go, Java, Python, Rust, or C++.
• Deep understanding of distributed systems concepts, including consensus, replication, partitioning, CAP theorem, and eventual consistency.
• Hands-on experience building and operating microservices at scale.
• Proven experience optimizing systems for performance, latency, scalability, and cost efficiency.
• Strong understanding of data structures, algorithms, and system design.
• Experience with cloud-native technologies such as AWS, GCP, or Azure, along with Kubernetes, Docker, and Terraform.
• Strong debugging, troubleshooting, and problem-solving skills, particularly in production environments.