
Job Description
We are AlgoTest (YC S22), a fintech startup founded in 2021 and headquartered in New Delhi, India. With over thousands of active traders on our platform, we are building India's leading ecosystem for options trading, empowering retail investors with tools for backtesting, paper trading, forward testing, and automated execution of algorithmic strategies.
About Our Engineering Team:
Our Engineering team is a small, high-ownership group of ~10 engineers who build and maintain the core infrastructure powering AlgoTest's trading platform. We obsess over high-reliability, low-latency systems for derivatives trading — from real-time order execution and data pipelines to backtesting engines and exchange integrations. Every engineer here works across the full backend stack, ships directly to production, and owns their systems end-to-end. We move fast, prioritise technical depth, and care deeply about building things that work flawlessly at scale. If you enjoy solving hard systems problems in a domain where performance truly matters, you'll thrive here.
Position Overview:
As an experienced Software Engineer, you will play a pivotal role in the development and implementation of our trading platform. You will work closely with the founders, and other engineers to build a scalable and user-friendly platform that meets the unique needs of retail traders.
Responsibilities:
* Architect and develop the core infrastructure of our platform, ensuring its scalability, reliability, and security.
* Write clean, maintainable, and efficient code.
* Collaborate closely with the team to define the technical roadmap and contribute to strategic decision-making processes.
Requirements:
* Bachelor's degree in Computer Science, Information Technology, or a related field. Advanced degree is a plus.
* Proven experience (2+ years) in software development, preferably in a fast-paced environment.
* Strong proficiency in backend and/or full-stack development, with expertise in web frameworks and technologies.
* Experience in designing and implementing RESTful APIs and microservices architecture.
* Familiarity with cloud platforms (e.g., AWS, Azure, GCP, DigitalOcean) and containerization technologies (e.g., Docker, Kubernetes).
* Solid understanding of database management systems (e.g., MongoDB, PostgreSQL) and proficiency in a SQL and a NoSQL DB.
* A self-driven and entrepreneurial mindset, with a willingness to take ownership and drive projects to successful completion.
Prior adventures/experience in the trading or financial industry, including knowledge of trading systems, market data, or algorithmic trading would be preferred.
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Interview Process
We value your time. Our process is efficient, transparent, and focused on practical backend aptitude:
1. Round 1 – Screening (<15 mins):
- What we look for: Your GitHub/portfolio and short answers on scaling and fintech trade-offs.
2. Round 2 – Tech Discussion + Machine Coding (1-1.5hr Call)
- The Call: Discussing a backend system you've built, API reliability, and concurrency.
- The Task: Machine Coding — design and implement a real-world trading system component under time constraints.
3. Round 3 – Bar Raiser (30 mins)
- What we look for: Cultural alignment, ownership mindset, and handling real-world startup challenges. This round evaluates depth of thinking, system design sensibility, and overall fit with AlgoTest's engineering culture. We’ll also go through your resume and ask a couple of technical/mathematical questions.
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Job Details
- Category
- Software
- Employment Type
- Full Time
- Location
- New Delhi, India
- Posted
- Compensation
- ₹1,800,000 - ₹3,500,000 per year
About AlgoTest
At https://algotest.in/, we are continuously building tools to help retail traders make better decisions for their investments. Our first product is a free options backtester for India. Our experience in the markets spans geographies and market segments - strategies we've worked on range from electronic options market-making in some of the deepest options markets in the world (CBOE, AMEX, PHLX, ARCA, ISE), to backtested factor-based market-taking strategies in NSE's F&O segment.
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