Locations: New York, New York
Job description
About this role
Aladdin is BlackRock’s unified technology and data platform used by BlackRock and many of the world’s largest Asset Managers and Investors.
The Aladdin Platform
Engineering organization is the Engineering Pillar within Aladdin responsible for building and operating the technology platform that powers Aladdin and includes the Developer Platform, the Core Platform and the Control Platform.
Within Aladdin Platform
Engineering, we are looking to bring on a senior technology leader to be the Head of AI Developer Platform.
Responsibilities
- Define and operationalize an AIfirst, agent driven SDLC embedded into the Developer Platform, spanning design, build, test, release, and operate phases, including:
- Agent assisted design, code generation, refactoring, and documentation
- Agent driven test generation, coverage analysis, defect intelligence, and built-in quality and resilience signals
- Intelligent release validation, change risk assessment, and deployment readiness
- Continuous functional, integration, regression, performance, and resilience testing orchestrated as first-class SDLC stages rather than post hoc controls
- Continuous learning loops that improve software, delivery workflows, and AI agents over time
- AI Vendor, Tooling & Platform Integration
- Drive evaluation, selection, and governance of AI developer tools and vendors integrated into the AI Developer Platform, ensuring capabilities are secure, production grade, and aligned to Aladdin’s architecture, risk posture, and engineering standards.
- Ensure AI tools are platform integrated rather than point solutions, delivered through standardized onboarding, quality gates, observability, lifecycle management, and Responsible AI controls in partnership with Risk, Security, Legal, and Architecture.
- Lead adoption of PDLC agents delivered through the Developer Platform, aligned to core engineering personas and architecture/design principles:
- Developers:
- Ensure quality, resilience, and risk prevention are embedded as default behaviors within PDLC agents, rather than treated as separate processes or late-stage controls.
- Performance, load, spike, and concurrency testing integrated into CI/CD pipelines
- Chaos engineering and fault injection experiments executed in preproduction environments
- Game Day testing and operational readiness simulations to validate incident response, observability, and recovery paths
- Establish clear skill expectations and enablement paths for developers, testers, and operators working in an AI augmented delivery model,
- Own the workforce enablement and distribution layer for the Developer Platform (through IDEs), ensuring AI capabilities and PDLC agents are delivered as secure, reusable, composable platform services within Engineering Services rather than fragmented tools.
- Lead context engineering and context graph strategy for the Developer Platform, including:
- Defining and evolving enterprise context graphs
- Ensuring AI agents and PDLC agents have governed access to the right context at the right time, with controlled blast radius
- Driving reuse of context primitives across SDLC, agent-based validation, and operational workflows
- Production aligned preproduction environments that enable reliable end-to-end validation
- Repeatable, governed test data strategies (refresh, reset/replay, synthetic data) that support functional, performance, and resilience testing
- Pre-Prod Environment stability, drift detection, and telemetry-based health signals as inputs to release decisions
- Be a Champion and Lead governance for context ownership, freshness, versioning, and reuse to prevent drift and repeated failures at scale.
- Build and lead a high-performance, globally distributed AI Developer Pla