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BlackRock

Associate/Vice President, AI Infrastructure Engineer

City of Edinburgh
Posted about 18 hours ago
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About This Role

At BlackRock, technology underpins everything we do. AI is a core strategic priority for the firm, embedded across Aladdin and our investment, client, and operational platforms. We are seeking an AI Infrastructure Engineer to help build and operate the foundational infrastructure that enables AI systems to scale safely, securely, and reliably across the enterprise. This role sits within Aladdin Platform Engineering and focuses on the infrastructure and platform services required to support machine learning models, large language models (LLMs), and emerging AI capabilities in production. The successful candidate will work closely with AI Engineers, Data Scientists, Platform Engineers, Security, and Product partners to deliver resilient, cloud native AI platforms in a highly regulated environment.

Key Responsibilities

  • Design, build, and operate AI focused infrastructure platforms supporting model development, training, evaluation, and inference.
  • Engineer scalable, reliable, and secure cloud native services to support AI workloads across AWS, Azure, and hybrid environments.
  • Partner with AI Engineering and Data Science teams to improve developer experience, performance, and operational stability of AI systems.
  • Enable production deployment of ML models and LLMs within governed enterprise environments, aligned with firmwide risk and compliance standards.
  • Implement and maintain infrastructure as code and automation to ensure repeatable, auditable platform provisioning.
  • Build and operate observability, monitoring, and alerting solutions for AI platforms, ensuring availability, performance, and cost transparency.
  • Collaborate with Security and Risk partners to integrate identity, access controls, data protection, and governance into AI infrastructure.
  • Contribute to architectural decisions and technical standards for AI platforms across Aladdin.
  • Participate in on-call rotations and operational support as required for critical platforms.
  • Continuously evaluate emerging AI infrastructure technologies and apply them pragmatically within BlackRock’s enterprise context.

Qualifications

Required

  • Strong experience in cloud infrastructure, platform engineering, or systems engineering roles.
  • 4+ 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.
  • Understanding of ML platform operations and governance concepts, including model deployment strategies, lifecycle management, monitoring/observability, and Disaster Recovery.
  • Experience supporting LLMs, generative AI platforms, or model serving infrastructure.
  • Experience supporting AI and machine learning workloads, with exposure to managed compute for model training and finetuning, experimentation over large datasets, and end-to-end MLOps pipeline flow including data ingestion, training, validation, and deployment.
  • Proficiency with Infrastructure as Code tools (e.g., Terraform, ARM/Bicep, CloudFormation).
  • Strong programming or scripting skills (e.g., Python, Bash, or similar).
  • Experience building and operating containerized and Enterprise-grade container orchestration platform supporting declarative infrastructure and horizontal scaling based platforms.
  • Solid understanding of reliability, scalability, observability, and operational best practices.
  • Ability to work effectively in cross-functional teams and communicate complex technical concepts clearly.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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It searches the market for you

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Preferred

  • Familiarity with GPU or accelerator-based infrastructure.
  • Experience working in financial services or other highly regulated industries.
  • Familiarity with multicloud architectures and enterprise governance requirements.

Our Benefits

To help you stay energized, engaged, and inspired, we offer a wide range of employee benefits including:

  • Retirement investment and tools designed to help you in building a sound financial future.
  • Access to education reimbursement.
  • Comprehensive resources to support your physical health and emotional well-being.
  • Family support programs.
  • 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.

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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 guidance on when and how to use AI during our hiring process so you can approach each step with confidence and showcase your best self.

About BlackRock

At BlackRock, we are all connected by one mission: to help more and more people experience financial well-being. Our clients, and the people they serve, are saving for retirement, paying for their children’s educations, buying homes, and starting businesses. Their investments also help to strengthen the global economy: support businesses small and large; finance infrastructure projects that connect and power cities; and facilitate innovations that drive progress.

This mission would not be possible without our smartest investment – the one we make in our employees. It’s why we’re dedicated to creating an environment where our colleagues feel welcomed, valued, and supported with networks, benefits, and development opportunities to help them thrive.

To learn more about BlackRock, please visit Careers.BlackRock.com. We also encourage you to get to know us on LinkedIn, Instagram, YouTube, X, and TikTok.

BlackRock is proud to be an Equal Opportunity Employer. We evaluate qualified applicants without regard to age, disability, race, religion, sex, sexual orientation, and other protected characteristics at law.

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Skills

Cloud Infrastructure
Platform Engineering
Systems Engineering
AWS
Azure
GCP
Machine Learning
Model Deployment
Infrastructure as Code
Python
Containerization
Observability
Security
Data Protection
Governance
MLOps

Location

City of Edinburgh, Scotland, United Kingdom

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