Business Overview

PMGTechis 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. Itoperatesas 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).

PMGTechleads 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 ofPMGTech, you will work directly with investment researchers and portfolio managers to build and scale capabilities in data engineering, GenAI, and platform toolingthatstreamlinesresearch workflows and enablesdifferentiated 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,researchplatformsand insights seamlessly to investors and researchers. Embedded withinDS&Sresearch pods- asset-class focused sub-teams -thisrole requires collaboration with AI Product leads, data leads and the investor teamstotransformresearchworkflows into intuitive,interactiveand resilientproduction-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 willintegrate data, analytics, and AI capabilities into user interfaces that enhance investment decision-makingat scale.

This rolerequiresexpertiseinmodern applicationdevelopmentframeworks across the stack (Python APIs, AI/LLM services,Cloud dataplatforms,data pipelines,production deployments,CI/CDandmodernwebapplication andUI frameworks).

Key Responsibilities

• Design, build and deploy investor research apps end_to_end owningfrontend,backend APIs, data/AI features, and intuitive UIs that fit investor workflows.

• Partner withtheResearchPod Leads and investorsto translatebusinessrequirementsinto product designanditerativelybuild high quality webapplications.

• Write reusable,maintainable,and extensible code, andcreatedocumentation 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 horizontalengineeringteams toleverageshared toolingandcontributeto buildingtools and development processesacross pods.

• Experience building production-grade full-stack applications with a modern Python backend (FastAPI, Flask, etc.) and TypeScript/JavaScriptfrontend (React/Next.js).

• Strong problem-solving, analytical, and software architecture skills.

• Experience deploying andoperatingfull-stack systems onCloud Platforms (GCP/Azure)including CI/CD, observability, andanalytics.

• Strong capability to translate business workflows into scalable technical designs and intuitive applications.

• Excellent communication skills, with the ability to gather requirementsfrom investors and product owners,collaborate and deliveriteratively,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 visualizationusing modern cloud platformssuch asBigQueryorSnowflake.

• Experience building applications with leading AI model providerssuch asOpen AI, Vertex, and/or Anthropic.

• Hands-on experience with analytics and AI/LLM features (prompt engineering, RAG/retrieval,agenticorchestration,LLMmonitoring, multi-modalityinputs)

• Experience building research, analytics, or portfolio/risk/market-data applications within investment management or broader financial services.