Vice President, DevOps Engineer , Lead Engineer

About this role Team Overview: Data is at the core of the Aladdin platform, and increasingly, our ability to consume, store, analyze, and gain insight from data is a key component of our competitive advantage. The Data Engineering team is responsible for the data ecosystem within BlackRock. We engineer high performance data pipelines, provide a fabric to discover and consume data, and continually evolve our data storage capabilities. We believe in writing small, testable code with a focus on innovation. We are committed to open source, and we regularly contribute our work back to the community. We are seeking top tier Cloud Native DevOps Platform Engineers to augment our Enterprise Data Platform team. Our objective is to extend our data lifecycle management practices to include structured, semi structured and unstructured data. This role requires a breadth of individual technical capabilities and competencies, though, most important, is a willingness and openness to learning new things across multiple technology disciplines. This role is for practitioners and not researchers. Position Summary: As a Data Platform Cloud/DevOps Engineer in the Data Engineering team, you will design, build, and maintain the cloud-native infrastructure that powers Aladdin's Enterprise Data Platform. You will enable data engineers, AI engineers, and application developers by providing scalable, reliable, and cost-efficient infrastructure for data processing, AI/ML workloads, and analytics services. Key Responsibilities: Infrastructure and Cloud Engineering Design, deploy, and manage cloud-native infrastructure across AWS, Azure, and private clouds Implement Infrastructure as Code (IaC) using Terraform, Ansible, and CloudFormation for repeatable, auditable deployments Manage Kubernetes clusters for scalable, reliable, and secure application and data workloads Deploy and configure service mesh, HashiCorp Vault, cert-manager, and other Kubernetes-native frameworks Design and implement network architectures including VPCs, load balancers, and ingress/egress controls Deploy and configure LLM serving platforms like MCP/agent orchestrators, chatbots, vector embedding services and secured API gateways for generative AI applications CI/CD and Automation Build and maintain CI/CD pipelines using ArgoCD, Azure DevOps, Jenkins, and GitHub Actions Implement GitOps workflows for automated, auditable infrastructure and application deployments Automate repetitive operational tasks using Python and Bash to improve team efficiency and reduce manual errors Develop self-service infrastructure provisioning capabilities for engineering teams Maintain version control best practices and collaborative development workflows Build and maintain MLOps CI/CD pipelines for automated model deployment to production environments Site Reliability Engineering (SRE) Implement monitoring, logging, and observability solutions using Prometheus, Grafana, ELK Stack, and Datadog Define and track Service Level Objectives (SLOs), Service Level Indicators (SLIs), and error budgets for data platform services Build automated alerting systems to proactively detect infrastructure issues and performance degradation Perform capacity planning and performance tuning for production infrastructure Conduct reliability analysis and implement preventive measures to improve system uptime Collaborate with operational teams on incident escalation and system reliability improvements Implement chaos engineering practices to test infrastructure resilience and fault tolerance Cloud Cost Optimization and FinOps Monitor and optimize cloud infrastructure costs across AWS, Azure, and private cloud environments Right-size compute, storage, and networking resources based on utilization metrics and cost-performance analysis Develop cost dashboards and reports to provide visibility into infrastructure spending trends Collaborate with finance and engineering teams on cloud budget planning an ... (truncated, view full listing at source)