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Rust AI Platform Engineering Director

Macpower Digital Assets Edge Private Limited

New York, NY

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JOB DETAILS
SALARY
$215,000–$275,000 Per Year
SKILLS
Agile Programming Methodologies, Amazon Web Services (AWS), Apache Cassandra, Apache Kafka, Apache Spark, Application Programming Interface (API), Artificial Intelligence (AI), C++ Programming Language, Cloud Computing, Computer Science, Continuous Deployment/Delivery, Continuous Integration, Data Processing, Data Science, Distributed Computing, Diversity, Docker, Documentation, Emerging Technology, Finance, GCP (Good Clinical Practices), GPU (Graphics Processing Unit), GitHub, Identify Issues, Investment Management, JAX (Java API for XML), Jenkins, Machine Learning, Microservices, Microsoft Windows Azure, Network Security, NoSQL, Problem Solving Skills, Programming Languages, Python Programming/Scripting Language, Quality Engineering, Requirements Management, Scalable System Development, Software Development, Software Development Lifecycle (SDLC), Software Engineering, Team Player, Technical/Engineering Design, Testing
LOCATION
New York, NY
POSTED
9 days ago
We are looking for highly motivated and determined engineers to set and drive a clear AI Software Strategy, delivering cohesive AI experiences across the firm. You will have the opportunity to work with some of the brightest minds in the industry, leveraging your insights and expertise to advance AI Platform Engineering. We value diversity and believe it is the key to our success, ensuring that your unique skills, curiosity, and passion are nurtured. Join us and grow both technically and personally while working at one of the most recognized financial companies in the world as part of an AI software development team.
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.
  • Familiarity with event-driven architecture and messaging frameworks like Kafka.
  • Experience with NoSQL datastores like Cassandra.

About the Company

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Macpower Digital Assets Edge Private Limited

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