Algo Engineer (GenAI Focus), Liability Driven Investment (LDI), Associate
BlackRockGurugram, IndiaPosted 2 April 2026
Job Description
About this role
About the team
The Fixed Income Solutions (FIS) business at BlackRock sits within the Portfolio Management Group (PMG) and operates globally across London, New York, Atlanta, San Francisco, Gurgaon and Mumbai. FIS partners closely with clients to design, implement, and manage outcome‑oriented investment solutions.
The Liability Driven Investment (LDI) business is a distinct part of FIS which leverages the breadth and depth of the entire platform when delivering investment solutions for our clients. BlackRock has been managing LDI mandates for over 20 years. We are passionate about designing and implementing fixed income solutions to help, primarily, pension fund clients to meet their long-term investment objectives. Our day to day activities range from monitoring the markets, modelling solutions and formulating the investment proposition, to trade construction, to designing the operational structure of the mandate and working with multiple BlackRock teams to implement it.
LDI Technology is a dedicated technology team embedded within the LDI business. The team’s mandate is to materially improve LDI investment and client workflows by building high‑quality, scalable, and well‑governed technology solutions.
Role overview
We are seeking an Associate level technologist to join the LDI Technology team.
This role is focused on designing, building, and maintaining Python‑based technology used across the LDI business, with a significant proportion of time dedicated to Generative AI initiatives. The successful candidate will help identify GenAI opportunities, build prototypes, and develop production‑ready solutions, including defining the data models and data strategy required to support them.
The role is suited to a hands‑on engineer who has a keen interest in working closely with the business, taking ownership of real problems, and applying engineering and AI techniques to investment workflows.
Key responsibilities
Design, implement, and maintain Python‑based platforms and tools supporting LDI investment and client workflows.
Work end‑to‑end across the development lifecycle: requirements gathering, development, testing, deployment, and production support.
Apply strong software engineering rigor, including version control, testing, documentation, and monitoring.
Debug and resolve complex technical issues across applications, data, and infrastructure.
Generative AI and data strategy
Identify, prototype, and implement Generative AI use cases across LDI investment, analytics, and operational workflows.
Design and build the data models required to support GenAI‑enabled tools, including defining how data should be structured and used.
Source, obtain, curate, and store internal data, building and maintaining proprietary datasets to support analytics and GenAI applications.
Progress successful GenAI experiments into robust, well‑governed production solutions.
Partner with internal technology and governance teams to ensure solutions meet BlackRock’s control, security, and data standards.
Business partnership
Develop a strong understanding of LDI investment processes and the data that underpins them.
Work closely with investors and LDI colleagues to identify high impact technology opportunities.
Support users in adopting new technology and integrating it into established workflows.
Guide less experienced colleagues by collaborating closely, forming emerging approaches, and building out a common code library
Partner with firmwide technology platforms, including Aladdin, to shape requirements, support testing, and integrate new capabilities into the LDI business.
Skills and experience required
Essential
Quantitative or technical background (Bachelors in Computer Science, Engineering, Mathematics, or a related field).
Strong Python experience, with the ability to build production‑grade tools.
Experience working across the full software development lifecycle.
Hands‑on experience with Generative AI and d ... (truncated, view full listing at source)
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