Director, Data ArchitectureEngineering

About this role

Responsible for preparing the big data infrastructure to be analyzed by Data Scientists and Analysts. Designs builds integrates tests and maintains highly scalable data management systems with data from various sources and then writes complex queries to ensure data is easily accessible and analytics work smoothly. May employ a variety of languages and tools to integrate new data management technologies and software engineering tools into existing structures. May work closely with others to determine what data management systems are appropriate and is responsible for problem-solving database integration issues and handling messy unstructured data sets. The overall goal is optimizing the performance of the firms big data ResponsibilitiesDefine and drive the technical strategy and roadmap for applied AI capabilities within Hyperion aligning AI investments with business priorities across Private the architecture design and scaling of complex multi-agent workflows using frameworks such as LangGraph or similar orchestration the end-to-end lifecycle of AI applications from proof of concept to MVP to production deployment including data pipelines backend services and platform integration leveraging Agile methodologies to deliver iteratively and at the integration of LLM-powered capabilities into core business products and platform services ensuring high availability low latency resilience and robust evaluation frameworks to assess agent behavior trajectories decision quality and system performance with a strong focus on reliability explainability and business and enforce engineering best practices for applied AI including testing observability CI/CD model and prompt evaluation and production standards for responsible AI governance risk management and operational excellence appropriate for a regulated enterprise closely with product engineering data and business stakeholders to prioritize use cases translate business needs into scalable AI-enabled solutions and drive adoption across the mentor and lead a high-performing team of engineers and applied AI practitioners fostering technical excellence collaboration and continuous the development of reusable platform capabilities and patterns that enable scalable adoption of AI across products and workflows rather than one-off current with developments in the generative AI landscape and evaluate emerging tools models and frameworks for their practical application within QualificationsStrong proficiency in Python and modern software engineering practices including production design patterns CI/CD automated testing and observability for AI experience building and deploying stateful multi-step AI systems using agentic orchestration frameworks such as understanding of core NLP concepts including tokenization embeddings semantic search and information foundation in data science and experimentation including statistical modeling data preprocessing evaluation methodologies and experimental working with graph-based data structures and libraries such as NetworkX to model complex relationships workflows and understanding of RAG architectures retrieval pipelines and vector with Transformer architectures and approaches to fine-tuning adapting or evaluating language with AI/ML frameworks such as PyTorch or TensorFlow and with cloud-native deployment environments including Enterprise-grade container orchestration platform supporting declarative infrastructure and horizontal designing and integrating AI systems with enterprise backend platforms APIs and data and ExperienceBachelors or Masters degree in Computer Science Data Science Mathematics AI/ML or a related quantitative field.15 years of experience building and deploying engineering AI or ML systems end to end including recent experience delivering LLM-based applications or workflows in production.3 years of experience leading teams or large-scale cross-functional initiatives with a track record of driving technical delivery and organizational success leading complex technical programs managing multiple priorities and delivering high-quality solutions at scale within Agile product and engineering written and verbal communication skills with the ability to influence senior technical and business -on experience with prompt engineering RAG pipelines entity extraction embeddings/vector search model evaluation fine-tuning and backend interest in open-source language models and a track record of staying current with developments in the rapidly evolving generative AI in financial services asset management or private markets is of the private markets investment lifecycle and data landscape is a Leadership ProfileStrategic thinker with the ability to translate business priorities into scalable technical -on leader who can operate effectively across strategy architecture and people leader with experience mentoring senior engineers and building high-performing operating in a fast-moving environment with evolving priorities and emerging about building scalable platforms and reusable capabilities rather than isolated to engineering rigor responsible AI practices and measurable business outcomes.

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

BlackRocks 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 weve provided guidanceon 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 childrens 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. Its why were 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 . 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.