Job description About this role Business Overview PMGTech is the horizontal technology platform within BlackRock’s Portfolio Management Group (PMG), integrating investment research with advanced engineering, AI, and alternative data to make technology a direct driver of alpha. It operates as one global team across three verticals – Platform Strategy, Research Solutions (DS&S), and Platform Change (IPT) – partnering closely with the BlackRock Aladdin ecosystem and PMG investment leadership. This integrated model delivers a coherent tech strategy, strengthens the research community, and scales capabilities across regions, asset classes (Equities, Fixed Income, Multi-asset), and investment styles (discretionary and systematic). PMGTech leads PMG’s AI strategy by building an AI-ready research environment, unified data layer, agentic orchestration networks, and an investment-focused application 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 that streamlines research workflows and enables differentiated alpha-generative investment insights across PMG’s investment pillars. Job Purpose / Background The Full Stack Engineer builds end-to-end, AI-enabled research applications that deliver data, research platforms and insights seamlessly to investors and researchers. Embedded within DS&S research pods- asset-class focused sub-teams - this role requires collaboration with AI Product leads, data leads and the investor teams to transform research workflows into intuitive, interactiveand resilient production-gradeapplications. Full Stack Engineers combine front-end and back-end development skills with an understanding of research needs to build applications that fit naturally into how investors conduct research. Full Stack Engineers will integrate data, analytics, and AI capabilities into user interfaces that enhance investment decision-making at scale. This role requires expertise in modern application development frameworks across the stack (Python APIs, AI/LLM services, Cloud data platforms, data pipelines, production deployments, CI/CD and modern web application and UI frameworks). Key Responsibilities Design, build and deploy investor research apps end‑to‑end owning frontend, backend APIs, data/AI features, and intuitive UIs that fit investor workflows. Partner with the Research Pod Leads and investors to translate business requirements into product design and iteratively build high quality webapplications. Write reusable, maintainable, and extensible code, and create documentation for team members. Build modules, libraries and frameworks that can help scale building web applications based on similar patterns, Ensure that the web applications have the required instrumentation and observability that helps investors build confidence in operational health of the app. Act as a core pod member and coordinate with horizontal engineering teams to leverage shared tooling and contribute to buildingtools and development processes across pods. Skills & Experience Experience building production-grade full-stack applications with a modern Python backend (FastAPI, Flask, etc.) and TypeScript/JavaScript frontend (React/Next.js). Strong problem-solving, analytical, and software architecture skills. Experience deploying and operating full-stack systems on Cloud Platforms (GCP/Azure) including CI/CD, observability, and analytics. Strong capability to translate business workflows into scalable technical designs and intuitive applications. Excellent communication skills, with the ability to gather requirements from investors and product owners, collaborate and deliver iteratively, and produce clear documentation for non-technical partners. Qualifications B.S. / M.S. college degree in Computer Science, Engineering, or related subject area 3+ years hands-on software development exposure in full-stack applications. Nice to Have Proven ability to work closely with data engineering teams on high-volume data pipelines and data visualization using modern cloud platforms such asBigQuery or Snowflake. Experience building applications with leading AI model providers such as Open AI, Vertex, and/or Anthropic. Hands-on experience with analytics and AI/LLM features (prompt engineering, RAG/retrieval, agentic orchestration, LLM monitoring, multi-modality inputs) Experience building research, analytics, or portfolio/risk/market-data applications within investment management or broader financial services.

About Blackrock

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