AI Full Stack Engineering/Quantitative Modeling Director

About this role

BlackRock is one of the world’s preeminent asset management firms and is a premier provider of global investment management, risk management and advisory services to institutional, intermediary, and individual investors around the world. BlackRock’s mission is to create a better financial future for our clients. We have a responsibility to be the voice of the investor, and we represent each client fairly and equally. Constant communication with a diverse team of partners strengthens us and delivers better results for our clients. Continuous innovation helps us bring the best of BlackRock to our clients. BlackRock offers a range of solutions — from rigorous fundamental and quantitative active management approaches aimed at maximizing outperformance to highly efficient indexing strategies designed to gain broad exposure to the world’s capital markets. Our clients can access our investment solutions through a variety of product structures, including individual and institutional separate accounts, mutual funds and other pooled investment vehicles, and the industry-leading iShares® ETFs.

Key Responsibilities

AI & Agentic Architecture

• Architect and lead development of autonomous agent systems for credit analysis, including self-improving chat agents, event-driven orchestration, and feedback loops for continuous agent improvement
• Design and implement agentic AI workflows using supervised architectures (e.g., LangChain/LangGraph) that plug into BlackRock’s broader AI assistant platform
• Drive the technical vision for AI-powered credit intelligence features, balancing innovation velocity with responsible AI principles and production reliability

Knowledge Graph & Data Infrastructure

• Own and evolve the credit knowledge graph (3.5M+ company nodes, 53M+ relationships), ensuring data quality, scalability, and clean integration with upstream and downstream systems
• Lead data lake unification across multiple sources (regulatory filings, market data feeds, proprietary datasets), building reliable ingestion pipelines with high reconciliation accuracy
• Design APIs and data services to provide clients with novel ways of leveraging credit analytics and knowledge graph insights

Quantitative Credit Modeling

• Train, evaluate, and productionize ML models for credit risk — including graph neural networks for relationship-aware default prediction, Bayesian/MRF frameworks for modeling correlated defaults, and temporal convolutional networks for time-series credit signals
• Expand private credit analytics coverage to address client needs across direct lending, CLOs (collateralized loan obligations), BDCs (business development companies), and asset-based finance
• Maintain and enhance financial models following rigorous development lifecycle practices, including backtesting, validation, and ongoing monitoring

Engineering Leadership

• Lead a team of data scientists, modelers, and ML practitioners, fostering a culture of technical excellence, continuous learning, and operational rigor
• Drive execution across multiple workstreams with cross-functional partners in product management, platform engineering, and data teams
• Communicate technical concepts clearly to non-technical stakeholders, including investment professionals and senior leadership
• Attract, retain, and grow engineering talent, mentor team members across experience levels

Minimum Requirements

• A bachelor’s degree in quantitative discipline in mathematics, physics, mechanical engineering, electrical engineering, computer engineering, or similar.
• Advanced degrees or equivalent professional experience in engineering systems, AI/ML applications, or financial technology are strongly preferred
• Strong practical knowledge of products, modeling methodologies, and analytics in the rates and derivatives space.
• Experience with enterprise knowledge graph architecture.
• Excellent communication skills.
• Ability to work horizontally across various functions, including portfolio managers and traders, quantitative modelers, model risk governance, and risk management.
• 10+ years of industry experience.

Preferred

• Background in financial services, credit analytics, or private markets (private credit, CLOs, BDCs, leveraged finance) or a strong desire to learn the domain quickly
• Familiarity with enterprise investment management platforms (e.g., Aladdin, eFront, Bloomberg PORT, FactSet) or similar large-scale financial technology systems
• Experience with regulatory compliance frameworks relevant to financial technology (MiFID II, SFDR, FINRA reporting)


For New York, NY Only the salary range for this position is USD$225,000.00 - USD$285,000.00 . Additionally, employees are eligible for an annual discretionary bonus, and benefits including healthcare, leave benefits, and retirement benefits. BlackRock operates a pay-for-performance compensation philosophy and your total compensation may vary based on role, location, and firm, department and individual performance.


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.

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.

For additional information on BlackRock, please visit @blackrock | Twitter: @blackrock | LinkedIn: www.linkedin.com/company/blackrock

BlackRock is proud to be an equal opportunity workplace. We are committed to equal employment opportunity to all applicants and existing employees, and we evaluate qualified applicants without regard to race, creed, color, national origin, sex (including pregnancy and gender identity/expression), sexual orientation, age, ancestry, physical or mental disability, marital status, political affiliation, religion, citizenship status, genetic information, veteran status, or any other basis protected under applicable federal, state, or local law. View the EEOC’s Know Your Rights poster and its supplement and the pay transparency statement.

 

BlackRock is committed to full inclusion of all qualified individuals and to providing reasonable accommodations or job modifications for individuals with disabilities. If reasonable accommodation/adjustments are needed throughout the employment process, please email Disability.Assistance@blackrock.com. All requests are treated in line with our privacy policy.

BlackRock will consider for employment qualified applicants with arrest or conviction records in a manner consistent with the requirements of the law, including any applicable fair chance law.