Artificial Intelligence & Machine Learning Engineer, Director

At BlackRock, technology is fundamental to how we serve clients andoperateatscale. Aladdin—our industry‑leading, end‑to‑end investment management platform—embodies this by combining deep financial expertise with advanced data and AI capabilities.

We are seeking aDirector of AI Platform / Engineeringto providetechnical and strategic leadershipwithin theAladdin AI Engineering organization. In this role, you will be responsible for shaping the direction of Aladdin’s AI platform, leading high‑impact engineering initiatives, and ensuring the delivery of scalable, reliable, and responsible AI solutions across investment, operations, and data science workflows. 

This role requires a blend ofhands‑on technical depth,architectural leadership, andpeople and delivery leadership. You will work closely with senior engineering leaders, product managers, data scientists, and business stakeholders to translate AI strategy into production‑grade platforms and services.

Key Responsibilities

Technical & Architectural Leadership

• Set thetechnical vision and architecturefor Aladdin’s AI platform, including LLM‑powered and agentic AI systems. 

• Lead the design and evolution ofscalable AI/ML platform services, APIs, and microservices that support Aladdin’s global user base. 

• Drive architectural decisions across distributed systems, ensuring reliability, scalability, security, and operational excellence. 

• Establish and enforceengineering standards, design patterns, and best practicesacross AI platform teams. 

• Ensure AI solutions are built with strong considerations forgovernance, observability, resilience, and responsible AI. 

Delivery & Execution

• Own delivery outcomes for multiple concurrent initiatives, balancing near‑term execution with long‑term platform evolution.

• Partner with product management to define roadmaps, prioritize investments, and align execution with business outcomes.

• Oversee production readiness, including design reviews, risk assessments, release management, and operational support.

• Drive continuous improvement in engineering workflows, quality, and delivery predictability.

People & Organizational Leadership

• Lead, mentor, and develop senior engineers, technical leads, and managers.

• Build a strong engineering culture centered on ownership, rigor, collaboration, and technical excellence.

• Support hiring, onboarding, performance management, and succession planning.

• Act as a senior technical voice across leadership forums and architectural reviews.

Stakeholder & Cross‑Functional Collaboration

• Partner closely with platform, product, data science, and infrastructure leaders.

• Communicate complex technical concepts clearly to senior leadership and non‑technical stakeholders.

• Represent Aladdin AI Engineering in cross‑organizational initiatives and governance forums.

Required Qualifications

AI / ML‑Specific Qualifications

• Proven experience leading teams that buildAI‑driven platforms and applications, including solutionsleveraginglarge language models (LLMs),AI Agents,agenttoolsand agent skills.

• Strong hands‑on familiarity withLLM frameworkssuch asLangChain,LlamaIndex, Semantic Kernel, or equivalent.

• Experience with Google Agent Development Kit (ADK)or comparable agent frameworks, including designing, orchestrating, and operating agent‑based systems in production.

• Deep understanding ofagentic AI architectures, including multi‑agent coordination, tool invocation, and stateful reasoning workflows.

• Experience withprompt engineering and prompt tuningat scale, including performance, reliability, and safety optimization.

• Strong understanding ofML model evaluation, monitoring, and behavioral drift management in production systems.

• Experience integratingvector databases(e.g.,Faiss, Chroma) into AI system architectures.

• Solid understanding ofMLOpspractices, including model lifecycle management, deployment pipelines, and observability.

• Experience leveragingAInativecode editors and IDEs (e.g.,CopilotenabledIDEs,agentassisteddevelopment environments, or similarAIaugmentedtooling) to improve developer productivity, code quality, and delivery velocity.

• Experienceestablishingbest practices and guardrails for the responsible use ofAInativedevelopment tools, including considerations for security, IP protection, compliance, and code quality. 

• Ability to evaluate and guideadoptionof emergingAIpowereddeveloper tools, balancing innovation with maintainability, governance, and platform standards.

• Strong awareness ofresponsible AI principles, governance, and risk management when deploying AI systems in regulated environments.