Research Engineer, Portfolio Management Group (PMG Tech), Associate
- Location Mumbai, India
- Experience ~1-4 yrs
- Job type Full-time
- Posted 9 Oct 2026
- Qualification Master's / Bachelor's
You will be taken to BlackRock’s own careers page to apply. Job ID R265897.
Job description
About this role
Your team
Portfolio Management Group Technology (PMG Tech) is the horizontal technology platform within BlackRock’s Portfolio Management Group. The team integrates portfolio management, risk management, and quantitative workflows with advanced engineering, artificial intelligence, and data capabilities, making technology a strategic driver of investment and risk outcomes. Risk and Quantitative Analysis (RQA) provides independent oversight of BlackRock’s investment and enterprise risks through quantitative analysis, risk expertise, and evidence-based insights. In partnership with PMG Tech, RQA uses advanced engineering, artificial intelligence, and data platforms to enhance decision-making, strengthen risk management capabilities, and scale innovative solutions across investment, operational, technology, and enterprise risk domains.
Your role and impact As a Research (AI) Engineer, you will partner with RQA, PMG Tech, and business stakeholders to develop data workflows, analytics solutions, and artificial intelligence-assisted capabilities that transform risk and quantitative challenges into actionable insights. Embedded within a PMG Tech Pod, a business-focused, cross-functional team, you will collaborate with risk managers, quantitative analysts, artificial intelligence leads, and engineers. You will deliver high-quality data assets, analytical tools, and technology solutions that support risk management and informed decision-making. This role requires an understanding of business problems and risk workflows, along with the ability to translate requirements into scalable data solutions. You will use Python, Structured Query Language (SQL), cloud data platforms, workflow orchestration, and visualization tools to develop and operate data-intensive applications. You will also apply data quality practices, continuous integration and continuous delivery processes, and data operations to create reliable, production-grade solutions.