Rust AI Platform Engineering Director

Key Responsibilities

• Design, develop, and maintain the next generation of scalable AI platform for the world's best investment management technology platform.
• Implement and manage Kubernetes clusters for deploying AI models.
• Build platform abstractions to manage cloud-native infrastructure across AWS, GCP, or Azure environments.
• Build and maintain automated pipelines for continuous training, testing, and deployment of machine learning models, with integrated enterprise concerns.
• Ensure the security and compliance of the platform.
• Troubleshoot and resolve issues related to platform performance and reliability.
• Refine business and functional requirements and translate them into scalable technical designs.
• Apply quality software engineering practices throughout the software development lifecycle.
• Work with team members in a multi-office, multi-country environment.
• Stay updated with the latest trends and technologies in AI and cloud engineering.

Requirements

• B.S./M.S. degree in Computer Science, Engineering, or a related subject area.
• 10+ years of experience in software and platform engineering.
• Proficiency in designing and building scalable APIs and microservices.
• Strong proficiency in Kubernetes, including Helm charts, Kustomize, and custom resource definitions (CRDs).
• Hands-on experience with cloud platforms such as AWS, GCP, or Azure.
• Expertise in containerization technologies (Docker, containerd).
• Experience in CI/CD tools (Jenkins, GitHub Actions, ArgoCD).
• Knowledge of infrastructure such as code (IaC) tools like Terraform or CloudFormation.
• Solid understanding of networking concepts, security policies, and API gateways in cloud environments.
• Proficiency in production-grade programming languages such as Rust, K8's, Cloud Infra, CI/CD Tools, API, Microservices and C++.
• Decent understanding of distributed systems, cluster orchestration and management.
• Good knowledge of data science tools (e.g PyTorch, Jax, Numpy) and programming languages such as Python.
• Experience with monitoring tools (Prometheus, Grafana).
• Experience working in Agile development teams with excellent collaboration skills.
• Grit in the face of technical obstacles.

Nice to Have

• Building SDK Documentation, AI Infra and client libraries to support API consumption.
• Knowledge of distributed data processing frameworks ( Spark, Dask).
• Understanding of GPU orchestration and optimization in Kubernetes.
• Familiarity with MLOps and ML Model lifecycle pipelines.
• Experience with AI model training and fine-tuning.
• Good knowledge of event-driven architecture and messaging frameworks like Kafka.
• Experience with NoSQL datastores like Cassandra.