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Weekday AI

Sr Software Engineer - Risk

Bengaluru
Level
Senior

Not stated in the posting: salary, work type, visa.

Open. First seen 3 October 2026.

Apply on the company's site →

What this role asks for

Particular to this role

Linux

Rare in Weekday AI's other 299 open postings.

Standard for software engineering roles

Python

Common in software engineering postings at any company.

Read against Weekday AI's other open postings on this site.

The team: Weekday's Client via platform HIRES STEADILY

This role is one of 215 open in Weekday's Client via platform. 106 were posted in the last 30 days and the oldest in September: a team that hires all year rather than one being built.

WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS

Python (75 of 215), CI/CD (62 of 215), AWS (58 of 215), SQL (58 of 215), Azure (49 of 215), GCP (39 of 215), LLM (39 of 215)

OTHER ROLES ON THIS TEAM

From the team and dates on Weekday AI's own job board.

About the role

This role is for one of the Weekday's clients

Salary range: Rs 6000000 - Rs 7000000 (ie INR 60 - 70 LPA)

Min Experience: 4+ years

Location: Bengaluru, Karnataka, India
JobType: full-time

We are seeking a highly skilled Senior Software Engineer – Risk to design, develop, and enhance next-generation risk management solutions for institutional clients and internal teams. The role combines strong software engineering expertise with quantitative risk knowledge to build scalable, reliable, and high-performance risk technology.

You will work closely with risk professionals and engineering teams to evolve risk infrastructure, improve risk management processes, and develop robust solutions for complex trading environments.

Requirements

Key Responsibilities

  • Architect and develop scalable, reliable, and high-performance risk management solutions.
  • Design, build, maintain, and enhance proprietary risk tools, infrastructure, data platforms, and processes.
  • Develop technology solutions that balance speed, accuracy, scalability, and reliability.
  • Work closely with quantitative risk professionals and cross-functional engineering teams to improve the overall risk management technology stack.
  • Build robust systems capable of supporting institutional trading and risk management requirements.
  • Design and implement distributed systems and software architectures for complex risk applications.
  • Identify opportunities to improve system performance, reliability, automation, and operational efficiency.
  • Troubleshoot and resolve complex technical and risk-related issues.
  • Contribute to engineering best practices, system design, code quality, and technical documentation.
  • Mentor and coach engineers on developing, deploying, and maintaining risk technology solutions.
  • Take ownership of projects and drive them from design through implementation and production support.

Requirements

  • Bachelor's or Master's degree in Computer Science, Electrical Engineering, Financial Engineering, Mathematics, Physics, or a related technical discipline.
  • 4+ years of professional experience in quantitative risk, risk technology, or a closely related role.
  • Strong experience working with risk management systems in trading environments, such as hedge funds, investment banks, or financial institutions.
  • Good understanding of financial products and derivatives across multiple asset classes.
  • Strong software engineering fundamentals, including object-oriented programming, system design, and distributed architectures.
  • Strong hands-on programming experience with Python.
  • Experience working with Linux and AWS environments.
  • Ability to design and develop scalable, robust, and performant software systems.
  • Strong analytical and problem-solving capabilities.
  • Excellent communication and collaboration skills.
  • Proactive approach with strong ownership and ability to work effectively in a fast-paced environment.

Must-Have Skills

  • Quantitative Risk / Quant Risk
  • Risk Management
  • Python
  • Software Engineering

Good-to-Have Skills

  • Trading / Trading Systems
  • Derivatives
  • Distributed Systems
  • AWS
  • Linux

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