Artifical Intelligence Engineer, Portfolio Management Group, Vice President

plication layer to deploy AI-powered research solutions into production. As part of PMGTech, you will work directly with investment researchers and portfolio managers to build and scale capabilities in data engineering, GenAI, and platform tooling, streamlining research workflows and enabling differentiated, alpha-generative investment insights across PMG's investment pillars.

Job Purpose / Background

DS&S envisions the AI Lead Engineer role as an investor-facing technical partner role with deep AI, data, and systems expertise who designs and builds AI-powered research applications that integrate seamlessly into investor research workflows.

AI Lead Engineers will sit within DS&S pods - asset-class focused sub-teams - and collaborate directly with investors across Portfolio Management Group (PMG) to understand business requirements, map research workflows, identify opportunities for AI leverage, and translate them into intuitive, scalable, production-grade research applications.

AI Lead Engineers will own the technical vision, design, architecture, and product experience of specific research apps, partnering with Research Engineers, Engineering Hub and Platform to ensure these applications are robust, usable, and aligned with investor objectives.

Key Responsibilities

• Design architectures for AI-powered research applications leveraging Generative AI capabilities (RAG, agentic workflows, search, model fine-tuning).

• Partner with investors to translate open-ended research questions into feasible AI-driven product concepts.

• Be hands-on in leading the lifecycle from POC to MVP to production for AI applications, including data pipelines and backend integration.

• Own the end-to-end user experience of investor-facing research apps, including intuitive front-end UI designs.

• Evaluate emerging models and APIs; define best practices for prompts, safety, reliability, and testing with internal and external tech teams.

• Leverage enterprise data engines, orchestration frameworks, and secure/observable production practices with Engineering Hub and Platforms.

• Implement monitoring, observability, evaluation frameworks, and data-quality safeguards for GenAI-powered research applications.

Skills & Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or equivalent.

• 6+ years of work experience delivering ML, AI, and data-intensive systems.

• Hands-on experience building and deploying AI systems end-to-end - including LLM workflows, prompt engineering, RAG pipelines, entity extraction, embeddings/vector search, text2sql, fine-tuning, evaluation, and backend integration using Python and SQL.

• Strong written and oral communication skills and ability to work directly with investors and senior partners is a must.

• Domain specific experience is a plus - building data-driven / research applications for investment research, investment management or financial services.

• Hands-on experience with any major cloud platform, proficiency in front-end or full-stack development is a plus.

• Preference for prior experience with open-source language models and actively staying current with developments in the rapidly evolving generative AI landscape.

• Understanding of investment strategies and asset classes is a plus.

Key Attributes

• Deep curiosity about investment management and investment research.

• Ability to translate business and research needs into technical solutions.

• Technical leadership from concept to implementation.

• Strong product intuition and user-centric thinking.

• Ability to simplify complex AI systems into intuitive user experiences.

• High standards for quality, reliability, and safety in AI systems.

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: https://www.linkedin.com/company/blackrock

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.