We are looking for engineers with strong coding skills and solid computer science fundamentals who are passionate about building resilient, high-performance distributed systems and platform infrastructure.
As a Software Engineer in AI & Data Platform Reliability Engineering, you will work on systems powering GenAI, ML inference, and real-time fraud decisioning at scale. This is a hands-on engineering role focused on system design, platform development, and intelligent automation.
You will:
Design and build developer-first platform components that enable seamless onboarding and execution of ML workflows
Develop automation, internal tools, and AI-driven solutions to enhance observability, reliability, and operational efficiency
Build and operate multi-tenant, distributed systems handling high-throughput and highly concurrent workloads
Work on systems that scale to extreme traffic spikes (up to 100x BAU) with strict latency and availability requirements
Collaborate with cross-functional teams to deliver impactful platform capabilities and customer-facing features
Lead projects end-to-end—from architecture and design to deployment and production excellence
Continuously improve system performance, scalability, and resilience
Proactively identify, diagnose, and solve complex system and production challenges
We are looking for engineers who enjoy going deep into systems, understanding how they behave at scale, and building smart, scalable solutions on cloud-native infrastructure (Kubernetes, hybrid cloud).
Minimum Qualifications
Bachelor’s degree in Computer Science, Computer Engineering, or equivalent technical field
3+ years of strong programming experience in Python or similar languages
Solid foundation in data structures, algorithms, operating systems, and distributed systems fundamentals
Experience with cloud-native technologies (Kubernetes, containers, AWS or similar platforms)
Familiarity with infrastructure as code and automation tools (e.g., Terraform, Ansible)
Ability to read, understand, and work effectively with large open-source codebases
Preferred Qualifications
Excellent analytical & problem solving skills.
Exposure to Machine Learning and GenAI technologies.
Exposure to datasets management and cost optimisation in cloud.
Exposure to Ray and Ray Serve, for building scalable, distributed, and model-serving platform components.