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Goldman Sachs

The Core Engineering- BLR/HYD

Bengaluru, Karnataka, India

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hirly's read of this role

Seniority
Mid level
Country
IN
Work mode
On-site / unstated
First seen by hirly
27 Sept 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

Metrics & Analytics Platform - Portfolio Risk Platforms

Organization

The Core Engineering builds and operates the platforms, applications, data solutions, models, and analytics that power critical processes for the firm’s Risk, Controllers, Compliance, Corporate Treasury, Human Capital Management functions (The Core). A centralized engineering structure in support of The Core enables a common platform model and operating framework that promotes consistent governance and scalable solutions, leveraging cloud, AI, and machine learning for innovation and efficiency.

Metrics & Analytics Platforms, within The Core Engineering, is responsible for the measurement and management of the firm’s risk, capital, and liquidity for The Core functions. Within Metrics & Analytics Platforms unit, Liquidity and Trading Platforms team provide critical business services for Corporate Treasury across trading and liquidity execution to support the daily management of global cash and liquidity across all businesses.

Job Description

The Portfolio Risk Metrics & Analytics Engineering team within The Core Engineering designs, engineers, and maintains the high-performance risk workflows and calculation engines that generate critical risk metrics for global risk management teams.

We are seeking a highly skilled Software Engineer to join our dynamic team in Bengaluru/Hyderabad. In this role, you will focus on hands-on development, collaborating closely with team members and stakeholders to develop, scale, and maintain the systems driving our risk metrics and workflows.

Responsibilities

  • Build Scalable Metrics Engines: Develop and optimize high-throughput, reliable data and calculation processes that generate timely and accurate lending metrics to actively manage and mitigate the firm’s risk exposures.
  • Build Complex Risk Workflows: Engineer highly performant, resilient, and scalable systems that empower risk managers to seamlessly evaluate market scenarios, counterparties, assign credit ratings, and define risk appetites.
  • Implement Next-Generation Architecture: Contribute to the design and execution of our next-generation architecture with an AI-driven, cloud-first mindset—ensuring maximum resiliency, scalability, and alignment with the firm’s long-term strategic growth.
  • Hands-On Technical Implementation: Actively write clean, production-grade code, implement complex platform uplifts, and resolve technical challenges using modern programming languages and frameworks.
  • Adhere to Engineering Excellence: Follow modern SDLC practices, write robust unit tests, and participate in code reviews to maintain high code quality.
  • Collaborate Cross-Functionally: Partner closely with quantitative engineers, technical leaders across the broader engineering organization, and product managers to implement and execute our next-generation architecture.

Minimum Qualifications

  • Hands-on software development experience building and scaling enterprise-level, business-critical systems.
  • Strong hands-on experience with backend technologies such as Java, Spring Boot, Python.
  • Strong experience working with modern, scalable SDLC practices (CI/CD, automated testing, code reviews).
  • Hands-on experience with cloud technologies, preferably AWS, and building high-availability patterns.
  • Experience implementing or integrating AI-enabled tools, platforms, or automated solutions.
  • Exceptional analytical, debugging, and problem-solving skills.
  • A strong appetite and openness to dive into proprietary systems, understand their inner workings, and strategically uplift them.
  • Strong communication and interpersonal skills, with the ability to collaborate effectively with technical and non-technical stakeholders.
  • Bachelor’s degree in computer science, Engineering, or equivalent practical experience.

Preferred Qualifications

Prior experience in the financial services industry, with deep domain knowledge in Risk, or Risk Engineering systems.

Original posting on Goldman Sachs's site ↗

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