AI Quantitative Engineer/ Architect (Co-Founder | Partner Role)

Mangal Keshav Financial Services LLP

Chief Investment Officer (CIO)

next-generation AI-native fund architecture from scratch

build, own, and grow

Key Responsibilities:

• Architect and develop

  AI/ML models for derivatives trading strategies (Options, Futures)

  .
• Apply

  Reinforcement Learning frameworks

  for live market trading.
• Utilize

  PyTorch

  extensively in model development, optimization, and deployment.
• Lead system architecture, ensuring scalable real-time trading environments across

  Linux-based AWS cloud infrastructure

  .
• Read, understand, and implement

  API documentation

  for integrating data feeds (live & historical) from global vendors.
• Work on

  QuantConnect API integrations

  for both live trading and backtesting environments.
• Ensure deployed strategies are adaptable across

  NSE, BSE, CME, NYSE, CBOE

  , and other global exchanges.
• Collaborate directly with the CIO on fund structure, and scaling operations.
• Manage the complete lifecycle of model development — from backtesting to live deployment.
• Build a technology-first culture and lead future engineering hires.
• Contribute to the entrepreneurial journey, including strategic decision-making and business growth.
• You will have the

  freedom to architect the entire system from scratch

  to create a

  truly AI-native fund

  .

Qualification parameters:

• Minimum 7 years of hands-on experience in proprietary trading desks or hedge funds internationally with firms such as Jane Street, Renaissance Technologies, Citadel, Two Sigma, D.E.

  Shaw, Millennium Management

  , or equivalent.
• Experience of working in international markets of New York, London, Singapore, etc.
• Proficient in

  Python programming

  , with production-level coding experience.
• Extensive hands-on experience with

  PyTorch

  for model building, fine-tuning, and deployment (this is non-negotiable and will be assessed thoroughly).
• Solid understanding of

  Machine Learning (ML)

  and

  Reinforcement Learning (RL)

  applied in trading environments.
• Familiarity with

  Linux server environments

  and deploying applications on

  AWS infrastructure

  .
• Ability to work with

  API documentation

  for data integration and real-time feeds.
• Entrepreneurial mindset willing to join on a

  profit-sharing/ partnership model

  .

Preferred qualification parameters:

• Prior experience with QuantConnect

  or similar backtesting/live trading platforms.
• Prior experience working with cross-border teams (India and UAE) is advantageous.

While we understand that not every candidate may tick every single box, preference will be given to those who cover a majority of these requirements.

Compensation:

This is a Co-Founder / Equity Partner

equity stake/profit-sharing opportunity in the newly established fund entity

Location:

Full-Time | On-site | Dubai, U.A.E.