AI Infrastructure Engineer

About This Role YOUR TEAM Aladdin Platform Engineering powers the technology foundation behind BlackRock’s Aladdin platform - a unified system that connects risk, portfolio management, trading, and operations for investors globally. We build the mission critical hosting platform that enable engineers to develop products and operators to run the platform at scale.

Our teams sit at the center of how Aladdin evolves - partnering across product, data, and engineering to deliver scalable infrastructure that support mission-critical workflows for clients worldwide. We develop AI-first engineering capabilities, using a suite of tools across the development lifecycle to improve developer productivity and reduce friction at scale.

YOUR ROLE AND IMPACT As an AI-Enabled Infrastructure and Systems Engineer, you will combine deep infrastructure expertise with modern software engineering practices to design, build, and operate the platforms that power critical business capabilities. You will develop scalable, secure, and resilient solutions while automating their deployment, configuration, and lifecycle management through Infrastructure as Code, software development, and platform engineering principles. Your work will simplify complex operations, improve reliability, and enable teams to deliver technology faster, more consistently, and at greater scale.

You’ll pair strong engineering fundamentals with an AI-driven approach to solving problems—leveraging automation, intelligent tooling, and emerging AI capabilities to reduce operational toil, accelerate delivery, and enhance the developer experience. As a technical leader, you will help shape platform strategy, influence architectural direction, mentor engineers, and drive the adoption of next-generation engineering practices that define the future of Aladdin.

Your Responsibilities

• Architect and build scalable, reliable, and secure infrastructure across multi-cloud environments (AWS, Azure, GCP) that underpins Aladdin’s platform and application ecosystem
• Design AI focused infrastructure platforms supporting model development, training, evaluation, and inference.
• Lead automation initiatives using Infrastructure as Code (IaC) tools such as Terraform, Ansible, and CloudFormation to support mission-critical workloads
• Apply AI-assisted engineering approaches to reduce toil and enhance how software is built, tested, and operated
• Adopt a product-centric approach, treating internal platforms and automation frameworks as products with clear ownership, lifecycle management, and continuous improvement.
• Collaborate across global teams to solve complex technical challenges and deliver shared platform capabilities
• Contribute to system design, architecture decisions, and technical direction for key components and services
• Own execution and delivery of large-scale projects, balancing hands-on technical work with cross-functional collaboration across engineering, operations, and governance teams.
• Mentor engineers and help foster a collaborative, inclusive, and high-performing engineering culture

YOU HAVE…

• 5+ years of experience in infrastructure engineering, building and delivering production-grade systems
• Proven experience in cloud infrastructure, platform engineering, or systems engineering roles.
• Proficiency with Infrastructure as Code‑as‑code tools (e.g., Terraform, ARM/Bicep, CloudFormation).
• Strong programming or scripting skills (e.g., Python, Java, Golang, or similar).
• Hands-on expertise with AWS and/or Azure and/or GCP, including Azure ML, Azure Foundry, AWS Bedrock, Google Vertex, as well as cloud compute, networking, storage, and security services.
• Familiarity with modern development practices (testing, version control, CI/CD) and scalable system design
• Exposure to cloud-native architectures, microservices, or platform engineering concepts
• Experience supporting AI and machine learning workloads, with exposure to managed compute for model training and fine‑tuning, experimentation over large datasets, and end‑to‑end MLOps pipeline flow including data ingestion, training, validation and deployment.
• Interest or experience in applying AI/ML tools or AI-assisted development to enhance productivity or user experience
• Proven ability to own components end-to-end, lead technical work, and collaborate effectively across teams
• Strong problem-solving, communication, and curiosity - with an ability to learn quick…