BlackRock
AI Data Engineering Lead, Vice President
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About This Role
The VP AI Data Engineering Lead operates at the intersection of strategic influence, team leadership, and delivery excellence — playing a defining role in how AI-powered data and knowledge products are conceived, designed, and executed across the organization.
Leadership responsibilities include guiding a multi-team organization of AI agent engineers and data scientists, setting technical and delivery direction, building team capability, and ensuring accountability for production systems underpinning commercially viable knowledge products.
As the most senior bridge between Product Management, business stakeholders, and AI engineering, this role requires technical depth and strategic insight to shape product vision while ensuring engineering deliverables meet market needs and commercial outcomes.
Additionally, the successful candidate will establish engineering frameworks, author key principles, and foster a culture of quality, accuracy, and ownership across product leadership teams. Their expertise in agent workflow design, Vision AI, production validation, output-quality governance, and customer adoption is critical. Beyond delivery, they are visionary people builders, dedicated to developing high-performing teams and transforming current practices for future success.
For the successful candidate, impact is measured by sustainable commercial credibility, end-to-end accountability, and organizational capability.
Roles & Responsibilities
Team & Delivery Leadership
- Lead a team of AI agent engineers and data scientists, defining technical direction, managing delivery, enhancing team performance, and cultivating future talent.
- Own end-to-end solution design & delivery for complex AI features across multiple squads, ensuring alignment, consistency, and scalability in multi-agent, GenAI, and Vision AI workflows.
Strategic & Operational Influence
- Drive backlog prioritization, balancing customer impact with technical feasibility, model constraints, and team capacity.
- Set sprint planning, conduct stand-ups, and facilitate retrospectives to optimize team collaboration.
- Act as the bridge between Product Management, business stakeholders, and engineering to influence vision, feature definition, scope, and sequencing from both technical and commercial vantage points.
Partnering with Product Teams
- Collaborate with Product Managers to shape roadmaps, bringing in-depth technical insights and AI-specific influence on timing, feature efficacy, and quality criteria.
- Lead structured refinement sessions to ensure technical requirements are clarified and aligned for seamless development.
- Define and uphold quality standards for delivery, including extraction accuracy, edge-case coverage, agent behavior expectations, and non-functional requirements.
Post-Implementation & Commercialization
- Lead UAT, validation, and production monitoring, ensuring impactful adoption and customer readiness for rollouts.
- Support customer activation through quality validation cycles to ensure data/knowledge product effectiveness.
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Organizational Impact
- Develop standards for user story design, scale delivery frameworks, and champion best practices for AI-powered data products across the product organization.
- Assist in complex AI initiatives through discovery to delivery, addressing dependencies, risks, and stakeholder alignment.
- Mentor team members, conduct performance evaluations, and contribute decisively to hiring decisions for the engineering and data science teams.
- Identify bottlenecks in production workflows and drive institutional improvements targeting speed and quality.
- Foster and structure team growth, including hiring, onboarding, performance management, and career development at scale.
- Shape the operational design of the AI data engineering function as the organization expands.
Required Skills & Experience
Technical Skills
- Minimum 6–8 years of experience as an AI Engineering Lead, Program Lead, or Engineering Manager within SaaS, AI, or data-product enterprises, with 2–3 years at the senior principal level.
- Deep expertise in AI system design and scoping for GenAI, LLM-based, Vision AI solutions, and multi-agent workflows.
- Proficiency in scaled Agile methodologies, dependency management, and Agile tooling (Jira, Confluence, Miro) at companywide scale.
- Fluency in engaging with engineers and data scientists on architecture decisions, agent orchestration, prompt design, Vision AI trade-offs, and model behaviour.
- Completed end-to-end data and knowledge product lifecycles, including extraction accuracy for unstructured document, image, and multimodal data.
- Strong understanding of output-quality assurance models, set metrics for AI evaluation, human-in-the-loop review, and outcomes analysis.
- Grips on responsible AI principles, centering on data provenance, accuracy governance, and trust cultivation in commercialized outputs.
Non-Technical & Interpersonal Skills
- Executive-level communication skills to navigate engineering reviews and executive boardroom discussions with precision.
- Strong stakeholder engagement, driving alignment across product, commercial, and technical teams.
- Strategic acumen to transition tactical engineering decisions to long-term AI commercial strategy.
- Analytical mindset honing in on structured problem-solving, especially for data extraction and structuring challenges.
- Demonstrated emotional intelligence, building trust and inspiring engineers, scientists, and cross-functional groups.
- Deep financial services or data-product business fundamentals to gauge how product quality and timeliness correlate with client trust and revenue.
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Leadership & Ownership
- Track record in building, scaling, and mentoring AI-based technical teams, ensuring capability retention beyond single projects.
- Capacity to drive product vision and strategy, steering decisions on what gets built, not just how.
- Experience establishing long-lasting standards and frameworks within teams and organizations.
- Ability to balance technical excellence with robust delivery, addressing end-to-end accountability from inception to adoption.
- Proven history in mentoring career progression, managing performance, and hiring technical talent.
- Courage to advocate for accuracy, sustainability, and responsibility over speed, scope, or commercial semantics.
- Hands-on leadership in complex AI delivery outcomes, showcasing a dedication to post-launch validation and adoption.
- Competence in team building frameworks, including hiring, scaling, performance benchmarks, and succession planning.
What This Role Offers
- Leadship of a high-performing AI team working on globally impactful data and knowledge products, with tangible authority and autonomy.
- Strategic influence on organizational direction, partnering directly with executives on product vision, hiring, and operational models.
- Direct shaping of product/engineering tactics, feature prioritization, and commercial AI best practices.
- Chosen platform for building and pre-eminent expertise in AI engineering and leadership teams.
- Exposure to cutting-edge AI advancements, such as multi-agent architectures, GenAI, and Vision AI applied to real-world commercial challenges.
- Clear path toward C-level engineering roles with firm support for mentorship, external learning, and leadership burgeoning.
Benefits & Work Model
Organizational Support
- Comprehensive benefits including:
- Retirement savings tools, education reimbursement
- Health & wellness benefits, mental wellness resources
- Family support programs, Flexible Time Off
- Hybrid work model: Monthly engagement in the office with at least 4 in-office days/week. Flexibility allows hybrid choices, while office presence fosters critical consolidated moments.
- Equal Opportunity Employer commitment, reflecting diverse cultural backgrounds, skills, and protected characteristics.
Candidate AI Guidance
- BlackRock encourages thoughtful AI support in preparation and learning phases, but prioritizes discussions on candidate personal experience, judgment, and authentic problem-solving.
Please visit Careers.BlackRock.com to learn more about BlackRock’s mission-centric culture, benefits, and opportunities. Follow us on LinkedIn, Instagram, YouTube, X, and TikTok for insights into financial empowerment.
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