Job Description

Salary: $81,000 - 121,000 per year Requirements:

• We hold a B.S. or M.S. degree in Computer Science, Engineering, or a closely related discipline.
• We bring 10+ years of experience in software and platform engineering.
• We are skilled in designing and building scalable APIs and microservices.
• We have strong expertise in Kubernetes, including Helm charts, Kustomize, and custom resource definitions (CRDs).
• We have practical experience with cloud platforms such as AWS, GCP, or Azure.
• We are proficient in containerization technologies such as Docker and containerd.
• We have experience with CI/CD tools including Jenkins, GitHub Actions, and ArgoCD.
• We understand infrastructure as code tools like Terraform or CloudFormation.
• We have a solid grasp of networking concepts, security policies, and API gateways in cloud environments.
• We are proficient in production-grade programming languages such as Rust and C++.
• We have a strong understanding of distributed systems and cluster orchestration and management.
• We have good knowledge of data science tools such as PyTorch, Jax, and Numpy, as well as Python.
• We have experience using monitoring tools such as Prometheus and Grafana.
• We have worked in Agile development teams and collaborate effectively.
• We demonstrate persistence when facing technical challenges.
• Nice to have: We have built SDKs or client libraries to support API consumption.
• Nice to have: We understand distributed data processing frameworks such as Spark and Dask.
• Nice to have: We understand GPU orchestration and optimization in Kubernetes.
• Nice to have: We are familiar with MLOps and ML model lifecycle pipelines.
• Nice to have: We have experience with AI model training and fine-tuning.
• Nice to have: We are familiar with event-driven architecture and messaging frameworks such as Kafka.
• Nice to have: We have experience with NoSQL datastores such as Cassandra.

• We design, develop, and maintain the next generation of a scalable AI platform for a leading investment management technology platform.
• We implement and manage Kubernetes clusters for deploying AI models.
• We build platform abstractions to manage cloud-native infrastructure across AWS, GCP, or Azure environments.
• We create and maintain automated pipelines for continuous training, testing, and deployment of machine learning models, including enterprise requirements.
• We ensure the platform remains secure and compliant.
• We troubleshoot and resolve platform performance and reliability issues.
• We refine business and functional needs and translate them into scalable technical designs.
• We apply strong software engineering practices throughout the development lifecycle.
• We collaborate with team members across multiple offices and countries.
• We stay current with emerging trends and technologies in AI and cloud engineering.

• AI
• API
• AWS
• ArgoCD
• Azure
• CI/CD
• Cloud
• Cassandra
• Docker
• Fine-tuning
• GCP
• GitHub
• Grafana
• Helm
• Support
• Jenkins
• Kafka
• Kubernetes
• Kustomize
• Machine Learning
• MLOps
• Model Training
• NoSQL
• Prometheus
• PyTorch
• Python
• Rust
• Security
• Spark
• Terraform
• microservices
• numpy

More:

We collaborate with BlackRock to connect them with exceptional professionals for this role. You will join our AI Platform Engineering team within Aladdin Engineering, where we design, build, and run Aladdin and its associated products and platform services. This role sits at the center of our AI ecosystem and has the potential to shape the broader Aladdin application landscape. We offer the opportunity to work alongside highly talented professionals at one of the worlds most recognized financial technology companies, where we value diversity, curiosity, and technical growth in a multi-office, multi-country environment.

last updated 39 week of 2026

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