About this role

Are you interested in building innovative technology that shapes the financial markets? Do you like working at the speed of a startup, but want to solve some of the world’s most complex problems? Do you want to work with, and learn from, hands-on leaders in technology and finance?

Team Overview

This position requires a unique blend of hands-on systems knowledge, software development skills and team leadership. 

We are in search of a Principal Engineer to help lead Compute engineering.  This role requires a visionary leader and hands-on builder who is also able to collaborate globally to drive architecture and engineering excellence across the breadth of our organization. We seek a multi-disciplinary expert with a strong desire to mentor and effect organizational change.  We require this unique combination as we enhance the platform products and services that we host across multiple clouds for the larger Aladdin engineering community.

Position Overview:

We are seeking a Principal Engineer to join our Platform Engineering Cloud Managed Services team to help us design cloud platforms for mass adoption. The ideal candidate has 8+ years of platform engineering experience, including 5+ years working with cloud technologies (AWS, Azure, GCP), with a background in software engineering. This role focuses on designing and managing multi-cloud Platform-as-a-Service (PaaS) solutions, automating infrastructure with tools like Java,Python and Infrastructure-as-Code (IaC) tools, and implementing agentic AI (autonomous AI agents) to optimize cloud operations. The Senior Engineer will ensure our cloud architecture is scalable, secure, and aligned with best practices, while driving innovation in cloud automation and AI integration.

• Design & Deploy Multi-Cloud Services: Architect, implement, and manage platform services across AWS, Azure, and GCP, with a focus on PaaS components like object storage and database services. Ensure solutions are scalable, highly available, and cost-efficient while maintaining cross-cloud consistency.

• Infrastructure Automation: Develop and maintain automation scripts and frameworks using Python and Infrastructure as Code (IaC) tools (such as Infrastructure as Code (IaC) tools for provisioning cloud resources., CloudFormation). Build CI/CD pipelines to provision and update cloud resources reliably and repeatably.

• API Design & Data Modeling: Design and maintain robust APIs and underlying data models that enable seamless integration of platform services for mass adoption and scalability. Develop well-documented API endpoints (e.g. RESTful services) to allow internal teams and customers to easily consume platform features. Define and optimize data schemas to ensure consistency, performance, and adaptability as platform requirements evolve.

• Agentic AI Implementation:Integrate AI-driven automation into cloud operations – for example, implementing agentic AI systems that can monitor environments, make decisions, and take action with minimal human intervention (e.g. auto-remediation bots, intelligent scaling). Leverage these autonomous agents to reduce manual effort and improve platform resilience.

• Cloud Architecture & Security: Design and review cloud architectures to ensure secure, robust, and compliant solutions across multiple cloud providers. Apply best-practice cloud architecture frameworks to meet security and governance requirements (e.g. identity and access management, network segmentation, data encryption).

• Performance Optimization & Monitoring: Identify bottlenecks and implement optimizations (e.g. tuning databases or storage configurations) based on performance and reliability metrics. Utilize cloud monitoring tools and AIOps techniques to predict and prevent issues.

• Cross-Team Collaboration: Work closely with product engineering, core infrastructure, and security teams to understand requirements and integrate cloud services smoothly. Mentor junior engineers and share cloud best practices within the team. Coordinate with vendors and cloud provider support as needed to resolve complex issues.

• Innovation & Continuous Improvement: Stay up-to-date with emerging cloud technologies and services (including new PaaS offerings and AI tools). Evaluate and introduce new tools or practices (e.g. containerization, serverless, advanced analytics) that could enhance our managed platform. Drive continuous improvement in deployment processes, reliability engineering, and cost optimization.

• Experience: 8+ years of hands-on experience in platform engineering or cloud infrastructure roles, with at least 5 years focused on AWS, Azure, and/or GCP environments. Proven track record deploying and supporting production workloads on multiple cloud platforms.

• Multi-Cloud PaaS Expertise: Deep knowledge of PaaS services across major hyperscalers. This includes object storage systems (e.g. S3, Azure Blob, GCP Cloud Storage) and database technologies (relational and NoSQL managed databases) on each platform. Able to design cloud-agnostic solutions leveraging the best managed services from each provider.

• Automation & IaC Skills: Strong programming and scripting ability, particularly in Python, to automate tasks and integrate systems. Expertise in Infrastructure-as-Code tools such as Infrastructure as Code (IaC) tools for provisioning cloud resources. (preferred) as well as CloudFormation or ARM templates. Experience building fully automated infrastructure pipelines (CI/CD) for cloud resource provisioning and configuration.

• Cloud Architecture Proficiency: Solid understanding of cloud architectural principles and design patterns for scalability, resilience, security, and cost optimization. Capable of designing end-to-end solutions that meet business requirements while following cloud best practices (e.g. well-architected framework). Familiar with Compute products (VMs, Cloud-Native distributed containerized microservice orchestration., functions) as well as networking concepts (CDN, load balancing).

• Agentic AI / AI Ops Exposure: Experience implementing or working with AI-powered automation in infrastructure/cloud operations. This could include projects with agentic AI – systems that can autonomously analyze conditions and execute actions. Comfortable leveraging machine learning or AI tools to enhance monitoring, alerting, and self-healing of cloud services.

• Problem-Solving & Communication: Excellent troubleshooting skills across complex, distributed systems. Ability to analyze incidents in cloud environments and drive them to resolution. Strong communication skills to document designs and explain technical concepts to both technical and non-technical stakeholders. A collaborative mindset to work effectively within a diverse team.

• Enterprise Cloud Management: Prior experience in a Managed Services or enterprise cloud team, managing deployments at scale across multiple regions or accounts. Familiarity with ITIL or SRE (Site Reliability Engineering) principles for operating mission-critical services.

• DevOps & Containerization: Background in DevOps practices and tools beyond IaC – e.g. configuration management (Automation tools for configuration management and deployment, Chef) and containerization/orchestration (Open Container Initiative (OCI) container packaging and runtime, Cloud-Native distributed containerized microservice orchestration.). Experience deploying and running Cloud-Native distributed containerized microservice orchestration-based applications or using container services on AWS/Azure/GCP is a plus.

• Cloud Security & Compliance: Strong awareness of cloud security best practices and regulatory compliance (e.g. identity management, principle of least privilege, SOC2, GDPR). Experience implementing security controls or working with cloud security services (AWS IAM, Azure AD, Key Vault, etc.) is beneficial.

• AI/ML Technologies: Broader exposure to artificial intelligence or machine learning frameworks that complement agentic AI efforts. For example, familiarity with LLMs or AI APIs, monitoring tools with AI capabilities, or data analytics platforms in the cloud.

• Leadership & Mentorship: Demonstrated ability to lead technical projects or initiatives. While this is a hands-on role, an ideal candidate can guide junior engineers, champion best practices, and take ownership of complex deliverables. Strong organizational skills and the ability to work independently on strategic tasks are valued.

Our benefits

To help you stay energized, engaged and inspired, we offer a wide range of benefits including a strong retirement plan, tuition reimbursement, comprehensive healthcare, support for working parents and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.

Our hybrid work model

BlackRock’s hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person – aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock.

Guidance on AI use for candidates

At BlackRock, AI has long been part of how we work – enhancing decision-making, improving operations, and helping us deliver better outcomes for clients. We encourage candidates to use AI thoughtfully to learn, prepare, and work more effectively; but during our interview process, we want to focus on getting to know you through your own experiences, thinking, and judgment. To support you, we’ve provided  on when and how to use AI during our hiring process so you can approach each step with confidence and showcase your best self.