Artificial Intelligence & Machine Learning Engineer, Associate

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 agent based systems in production. Experience leveraging AI native code editors and IDEs (e.g., Copilot enabled IDEs, agent assisted development environments, or similar AI augmented 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 ... (truncated, view full listing at source)