BlackRock
Website:
blackrock.com
Company:
https://www.linkedin.com/company/blackrock
Seniority: Not Applicable
Industries: Financial Services
Job details:
About This Role
Role Overview:
We are seeking a senior, enterprise-minded Managing Director to lead AlphaGen Engineering as the accountable executive for the research product estate. This leader will set the strategic direction, operating model, and execution discipline required to modernize the end-to-end research lifecycle, reduce fragmented operational burden, and establish a single, scalable product engineering organization for AlphaGen’s next phase of growth.
As Managing Director, you will own the multi-year transformation agenda that advances AlphaGen toward a cloud-native, AI-first research ecosystem. You will partner with senior leaders across PMG, AlphaGen, Aladdin product, platform engineering, risk, security, and enterprise governance to retire legacy tooling, modernize core runtimes, and create productized self-service workflows that shorten research-to-production from months to hours. The role requires executive judgment, commercial orientation, and the ability to translate firm-wide priorities into durable engineering outcomes.
AlphaGen Investor Research Product is PMG’s strategic research-technology engine. This role will be responsible for shaping and delivering a cloud-native, AI-powered, self-service suite of products that accelerates the lifecycle of data, signals, and models, while working in deep partnership with the AlphaGen platform team to ensure the operational backbone meets enterprise standards for reliability, resiliency, security, cost discipline, and scale.
Key Responsibilities
Strategic Leadership & Transformation Execution
- Enterprise Strategy & Execution: Define and execute the enterprise product engineering strategy for AlphaGen Investor Research, aligning product direction with major firm priorities including cloud migration, AI-first workflows, standardization, resilience, operational risk reduction, and legacy system retirement.
- Executive Accountability: Establish clear ownership, decision rights, funding priorities, governance, and measurable outcomes across the full AlphaGen investor research product estate, ensuring senior stakeholders have transparency on progress, trade-offs, risks, and value delivery.
Partnership Building & Cross-Functional Collaboration
- Senior Stakeholder Partnership: Build trusted partnerships with PMG, AlphaGen leadership, Aladdin product, platform engineering, enterprise architecture, risk, security, finance, and governance stakeholders to align roadmaps, resolve dependencies, and drive shared outcomes across organizational boundaries.
- Governance & Control Environment: Strengthen collaboration with internal governing bodies and central teams to ensure consistent engineering standards, regulatory compliance, audit readiness, operational resilience, and seamless integration with broader enterprise systems.
User Engagement & Adoption (Self-Service by Default)
- User-Centric Product Strategy: Set the product strategy for a “single front door” research experience that enables researchers to access data, tools, documentation, support, and production pathways through a cohesive, intuitive, and scalable operating model across the full spectrum of research personas.
- Frictionless Research-to-Production: Deliver a materially simpler research-to-production pipeline by productizing reusable building blocks for data onboarding, signal development, model validation, production release, controls, and support, enabling researchers to move from idea to production with minimal hand-offs and clearer accountability.
Product Engineering Leadership (What Researchers Use)
- Core Frameworks & Developer Experience: Own and evolve the core libraries, frameworks, SDKs, APIs, templates, and archetypes that enable consistent signal and model development, ensuring researchers have a cohesive, high-quality development experience at enterprise scale.
- AI-Enabled Tooling: Lead the development of AI-powered research tools and automation, including spec-to-signal workflows, validation agents, automated quality checks, and intelligent controls that shift scaling from people-driven processes to platform-driven capabilities.
- Model Lifecycle Governance: Own end-to-end model lifecycle governance tooling from experiment to validation to production, including configuration management, metadata tracking, reproducibility, approvals, controls, and evidence required for enterprise governance.
Product Infrastructure Leadership (Systems the Platform Runs On)
- Foundational Systems Partnership: Partner with the AlphaGen platform team to optimize the foundational systems that power AlphaGen products and ensure product needs are reflected in platform investment, prioritization, and operating standards.
- Compute & Runtime: Shape scalable GPU/CPU execution environments, efficient scaling policies, performance optimization, and resource allocation models for diverse and cost-sensitive research workloads.
- Observability & Operations: Drive end-to-end telemetry, monitoring, incident detection, recovery automation, service health transparency, and operational discipline required for high platform uptime and resiliency.
- DevOps & CI/CD: Champion infrastructure-as-code, robust deployment pipelines, standardized build/test/release workflows, and disciplined change management to accelerate delivery while improving reliability.
- Reliability & Production Standards: Apply resiliency patterns and harden systems to enterprise production standards for security, stability, auditability, and operational risk management.
- Operational Automation: Expand automation for data quality checks, pipeline health monitoring, backfills, change management, support workflows, and control evidence to reduce manual intervention, key-person dependency, and execution risk.
Legacy Modernization & Tech Stack Evolution
- Cloud Migration & Modernization: Serve as the executive owner for the product modernization journey, including migration from legacy systems to cloud-native architectures, rationalization of overlapping tools, and timely retirement of platforms that create cost, risk, or operational drag.
- Next-Generation Platform Architecture: Drive an API-first, cloud-native platform design that improves scalability, performance, interoperability, and extensibility across the ecosystem. Leverage AI/ML where it materially improves speed, quality, control, operational insight, and user experience.
Market and Business Insight / “North Star” Alignment
- Industry, Client, and Internal Insight: Stay attuned to market trends, investment research needs, technology shifts, and internal demand signals, including the rising need for adaptable alpha-generation platforms, AI-driven research capabilities, scalable compute, and resilient production pathways.
- Define and Operationalize the North Star: Partner with senior leadership to define, communicate, and operationalize the business “North Star” for AlphaGen Product Engineering: reduce operational barriers, enable rapid iteration, scale platform services, improve control and resilience, and help the firm capture more alpha opportunities.
Qualifications
Education: Bachelor’s degree in Computer Science, Engineering, or a related field; or equivalent practical experience. Advanced degree preferred.
Executive Engineering Leadership: Significant experience leading large, senior engineering organizations through complex product and platform transformation initiatives, including cloud migration, operating model redesign, AI-enabled modernization, production resilience, and legacy retirement. Demonstrated ability to set enterprise vision, secure alignment, manage investment trade-offs, and deliver measurable outcomes across multi-year programs.
Technical Depth
- Alpha generation workflows or closely related quantitative research processes in finance/investments.
- Cloud technologies and cloud-native architectural patterns (e.g., microservices, containerization, distributed computing e.g. Ray).
- API-first platform design and developer experience best practices.
- AI/ML applications for workflow automation, data validation, and operational excellence
- Modern stack knowledge and skills – e.g. Python, Polars, Ray, MLFlow or equivalent technology
Executive Influence & Collaboration: Demonstrated strength building senior partnerships and influencing across product, platform, infrastructure, investment, governance, risk, security, and finance stakeholders. Able to align senior leaders around a common vision, roadmap, funding model, and operating discipline.
Execution in Complexity: Proven ability to operate in complex market, technology, and organizational contexts, translating strategic objectives into accountable execution plans. Track record of driving innovation, navigating ambiguity, managing risk, and delivering measurable enterprise outcomes at scale.
People Leadership: Experience attracting, developing, and retaining senior technical talent; building high-performing leadership teams; setting clear standards; and creating an inclusive, accountable culture that scales beyond individual dependency.
Leadership Attributes
This role will set the tone for how AlphaGen Product Engineering operates, scales, and partners with the business. The leader should demonstrate the following attributes consistently:
- AI-First, Human-in-the-Loop: Embraces AI-driven solutions as a default for efficiency, quality, and scale, while preserving expert human judgment in critical loops to ensure trust, control, and investment relevance.
- Platform Over People: Prioritizes robust platforms, automation, and operating discipline over reliance on individual heroic effort, enabling sustainable growth, resilience, and repeatability.
- Single Front Door: Advocates for a unified user experience where researchers and stakeholders have one intuitive entry point for data, tools, documentation, production pathways, and support.
- Standardization Everywhere: Drives consistency in tools, processes, controls, and data patterns, reducing complexity and improving interoperability, maintainability, and speed of execution.
- Self-Service as the Default: Champions self-service capabilities that empower users to accomplish high-value tasks independently, from data ingestion to model deployment, without bespoke engineering work wherever possible.
- Deep Co-Ownership with PMG: Builds a culture of partnership with the Portfolio Management Group, aligning on priorities, roadmaps, KPIs, investment outcomes, and shared accountability for platform value.
- Enterprise Stewardship: Operates with a firm-wide mindset, balancing innovation, speed, cost, risk, control, resilience, and talent development in every major decision.
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
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, family status, gender identity, race, religion, sex, sexual orientation and other protected attributes at law.
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