About this role
Joining BlackRock means becoming part of a firm that oversees more tha n $14 trillion in assets and operates at the intersection of finance and technology. As part of the Aladdin AI Engineering team, you will work with advanced technologies, collaborate with exceptional engineers, and help shape the future of AI‑driven investment management.
At BlackRock, technology has always been core to our mission. Aladdin—our industry‑leading, end‑to‑end investment management platform—embodies this vision by combining deep financial expertise with cutting‑edge data and AI capabilities.
We are seeking a highly motivated AI Platform / AI Product Engineer to join the Aladdin AI Engineering team. In this role, you will help build and evolve the AI ecosystem that powers Aladdin, enabling intelligent, scalable, and responsible AI solutions across investment, operations, and data science workflows. You will work closely with distributed engineering and product teams to transform advanced research and AI capabilities into production‑grade platform services.
Key Responsibilities
Design and build the next generation of Aladdin’s AI‑enabled investment management platform, supporting the full investment lifecycle and research workflows.
Build, evolve, and extend AI/ML platform services by leveraging existing AI infrastructure and frameworks.
Design, implement, and integrate scalable APIs and microservices to support AI‑driven use cases across the Aladdin application ecosystem.
Develop and deploy LLM‑powered and agentic AI systems, from concept through production.
Translate business and functional requirements into robust, scalable technical designs.
Collaborate closely with product engineering, data science, and platform teams to deliver end‑to‑end AI solutions.
Apply strong software engineering practices across the SDLC, including design reviews, code reviews, testing, documentation, and production support.
Contribute to platform resilience and operational stability through monitoring, debugging, and Level‑2 production support.
Work effectively in a multi‑office, multi‑country Agile environment and contribute to continuous improvement of engineering workflows.
Required Qualifications
AI / ML‑Specific Qualifications
Experience building AI‑driven applications, including solutions that leverage large language models (LLMs), AI Agents, agent tools and agent skills.
Hands‑on experience with LLM frameworks such as LangChain, LlamaIndex, or Semantic Kernel.
Experience with Google Agent Development Kit (ADK) or comparable agent frameworks, including designing, orchestrating, and operating agentbased systems in production.
Experience leveraging AInative code editors and IDEs (e.g., Copilotenabled IDEs, agentassisted development environments, or similar AIaugmented tooling) to improve developer productivity, code quality, and delivery velocity.
Understanding of agentic AI architectures, including multi‑step reasoning, orchestration, and tool‑based execution.
Experience with prompt engineering and prompt tuning, including iterative improvement based on feedback and performance.
Familiarity with ML model evaluation, including monitoring accuracy, reliability, and behavioral drift over time.
Experience working with or integrating vector databases (e.g., Faiss, Chroma) as part of AI solutions.
Understanding of MLOps concepts, including ML lifecycle pipelines, deployment, observability, and operationalization.
Awareness of responsible AI considerations, including governance, safety, and reliability when deploying AI systems at scale.
Core Engineering Qualifications
B.S. or M.S. in Computer Science, Engineering, or a related field.
Associate level: 2+ years of relevant experience
Strong hands‑on experience with object‑oriented programming, particularly Java and Python.
Proven experience designing and building scalable APIs and microservices in a production environment.
Strong understanding of distributed systems fundamentals, including service boundaries, reliability, and scalability.
Familiarity with event‑driven architectures and messaging frameworks such as Kafka.
Experience working with cloud platforms (Azure preferred; AWS or GCP acceptable).
Knowledge of containerization and orchestration technologies such as Docker and Kubernetes.
Experience with relational and NoSQL datastores, including Cassandra.
Strong understanding of Agile development practices, including collaboration, code reviews, testing, and documentation.
Ability to reverse‑engineer existing systems and work effectively in complex, evolving codebases.
Excellent communication and collaboration skills, with the ability to explain technical decisions and align across stakeholders.
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 [email protected]. 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.Top Skills
BlackRock San Francisco, California, USA Office
400 Howard Street, San Francisco, California, United States, 94105
Similar Jobs at BlackRock
What you need to know about the San Francisco Tech Scene
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
