4 Exchange Apis Jobs

As a Quantitative Developer at Alpha Genie Capital, you will play a crucial role in designing and implementing quant trading strategies, OMS/RMS modules, and market risk tools. Your responsibilities will include developing and optimizing quantitative trading models for various asset classes, building real-time risk management modules integrated into OMS/RMS systems, collaborating with traders and product managers, utilizing market data APIs, order execution systems, and low-latency infrastructure, conducting backtesting and performance analysis, and ensuring compliance with regulatory and risk policies. To excel in this role, you should hold a Bachelors or Masters degree in Computer Science, Mathematics, Financial Engineering, or a related field, have at least 3-5 years of experience as a Quantitative Developer in trading technology, possess strong programming skills in C++/Python, hands-on experience with exchange APIs (NSE/BSE), and proficiency in designing low-latency systems. Additionally, knowledge of risk management frameworks, experience in building RMS modules, and expertise in data structures, algorithms, and performance optimization are essential. Joining Alpha Genie Capital will offer you the opportunity to be part of a high-growth fintech company that is dedicated to building mission-critical trading infrastructure. You will work on co-located, low-latency systems used by top-tier traders, receive a competitive salary, performance bonuses, and have access to growth opportunities within the organization. If you are passionate about developing cutting-edge trading platforms, implementing innovative strategies, and working in a dynamic and collaborative environment, we invite you to share your resume with us or reach out to us directly.,

As a Quantitative Developer at Alpha Genie Capital, you will be instrumental in designing and implementing cutting-edge quant trading strategies, OMS/RMS modules, and market risk tools. Your expertise will contribute to the development of low-latency trading platforms and advanced risk management systems that empower professional traders and financial institutions to thrive in fast-paced markets. Your responsibilities will include designing, developing, and optimizing quantitative trading models for various asset classes, as well as building and maintaining real-time risk management modules integrated into OMS/RMS systems. Collaboration with traders, quants, and product managers will be essential to translate trading requirements into technical solutions. Additionally, you will work with market data APIs, order execution systems, and low-latency infrastructure, while conducting backtesting, simulation, and performance analysis of strategies to ensure compliance with regulatory and risk policies. To excel in this role, you should hold a Bachelors/Masters degree in Computer Science, Mathematics, Financial Engineering, or a related field, along with at least 3-5 years of experience as a Quantitative Developer in trading technology. Proficiency in programming languages such as C++ and Python is crucial, as well as hands-on experience with exchange APIs (NSE/BSE) and low-latency system design. Your knowledge of risk management frameworks, experience in building RMS modules, and proficiency in data structures, algorithms, and performance optimization will be key assets in this role. Joining Alpha Genie Capital offers you the opportunity to be part of a high-growth fintech company that is dedicated to building mission-critical trading infrastructure. You will work on co-located, low-latency systems used by top-tier traders, and benefit from a competitive salary, performance bonuses, and growth opportunities. If you are ready to make an impact in the world of quantitative development and trading technology, we encourage you to connect with us by sharing your resume at @.,

As a C++ Developer specializing in trading and risk management systems at Alpha Genie Capital, you will be responsible for designing and implementing quantitative trading strategies, OMS/RMS modules, and market risk tools. Your role will involve collaborating with engineering and product teams to deliver robust and scalable systems that empower clients to gain a competitive edge in fast-moving markets. Your key responsibilities will include: - Designing, developing, and optimizing quantitative trading models for equities, derivatives, and other asset classes. - Building and maintaining real-time risk management modules integrated into OMS/RMS systems. - Collaborating with traders, quants, and product managers to translate trading requirements into technical solutions. - Working with market data APIs, order execution systems, and low-latency infrastructure. - Conducting backtesting, simulation, and performance analysis of strategies. - Ensuring compliance with regulatory and risk policies in all systems developed. To qualify for this role, you should have: - A Bachelors/Masters degree in Computer Science, Mathematics, Financial Engineering, or a related field. - 3-5 years of experience as a Quantitative Developer in trading technology. - Strong programming skills in C++ and Python. - Hands-on experience with exchange APIs (NSE/BSE) and low-latency system design. - Knowledge of risk management frameworks and experience in building RMS modules. - Proficiency in data structures, algorithms, and performance optimization. Joining Alpha Genie Capital offers you the opportunity to be part of a high-growth fintech that is building mission-critical trading infrastructure. You will work on co-located, low-latency systems used by top-tier traders, while enjoying a competitive salary, performance bonuses, and growth opportunities. If you are interested in this exciting opportunity, feel free to DM us or share your resume at @.,

You are a skilled Quantitative Researcher who will be joining our team to develop advanced algorithmic trading strategies for cryptocurrency markets. Leveraging your deep quantitative skills, market insights, and statistical modeling, you will be responsible for researching, designing, and testing trading strategies that capture alpha in digital asset markets. Your key responsibilities will include researching and developing quantitative trading strategies for crypto markets across spot, perpetual futures, and derivatives. You will analyze market microstructure, order flow, and liquidity to identify trading opportunities. Additionally, you will design and implement statistical and machine learning models for signal generation, risk forecasting, and anomaly detection. It will be essential for you to perform extensive backtesting, simulation, and performance analysis using historical and live data. Furthermore, optimizing strategies for execution costs, slippage, latency, and market impact will be part of your responsibilities. Collaboration with developers to translate research into production-grade algorithmic trading systems is also a key aspect of the role. Monitoring live strategies and conducting post-trade analysis to refine and improve models, staying updated on market trends, blockchain analytics, protocol updates, and evolving market structure, and contributing to research documentation, strategy reports, and knowledge sharing within the team are also part of your duties. The required skills and qualifications for this role include a strong background in quantitative research, statistical modeling, or applied mathematics, solid programming skills in Python, R, or similar languages for data analysis and prototyping, experience with time series analysis, signal processing, and statistical inference, ability to work with large datasets, proficiency in data cleaning, feature engineering, and data visualization, understanding of trading concepts such as PnL attribution, Sharpe ratio, drawdown, and risk management, interest in cryptocurrency markets and familiarity with crypto-specific market dynamics, excellent problem-solving and critical-thinking skills, and ability to communicate complex quantitative ideas clearly to technical and non-technical stakeholders. Preferred qualifications for this role include prior experience in algorithmic trading or systematic strategy development (crypto or traditional markets), knowledge of crypto market microstructure, DeFi protocols, and blockchain data analytics, familiarity with exchange APIs, order types, and execution logic, experience with backtesting frameworks and simulation environments, machine learning experience applied to financial markets (e.g. feature selection, ensemble models, reinforcement learning), and an academic background in quantitative disciplines (e.g. Mathematics, Statistics, Physics, Computer Science, Engineering, Finance).,