Quant Strategy & AI Agent Intern

Amber Group is a global leading digital asset company providing crypto financial services to both institutional and high-net-worth investors globally.We offer best-in-class liquidity solutions and cutting-edge trading infrastructure across major exchanges, applications, and networks. With over $1 trillion in cumulative trading volume, our deep liquidity helps power the digital asset ecosystem.Beyond trading, our full-suite of offerings includes wealth management, lending and investing products. But at our core, we focus on building strong relationships and delivering personalized service to help clients navigate this fast-growing industry.At Amber, security is our #1 priority. We have invested years of effort and millions of dollars in cybersecurity, crypto-security, and operational security across the firm, with industry-leading certifications like SOC 2 Type II and ISO 27001.Powered by a 400+ team of traders, technologists and engineers operating 24/7 globally, our technology and research capabilities are world-class. Yet we remain entrepreneurial, always seeking fresh ideas and risks worth taking. We are always interested in people who have an appetite for taking calculated risk, demonstrate a high level of original thinking and intellectual curiosity.Key ResponsibilitiesIdea-to-Strategy Engine (NL-to-Quant): Design agent workflows that translate natural-language market views into actionable quant trading strategies (entry/exit signals, factor screens, position sizing).Backtesting & Strategy Diagnostics: Integrate agents with backtesting engines) to run simulations, interpret key metrics (Sharpe, Sortino, max drawdown, turnover), and flag flaws like overfitting or lookahead bias.Agent Quant Tooling: Build tool-calling interfaces connecting LLMs to market data APIs, risk factor models, and paper-trading environments.Strategy Guardrails & Risk: Implement deterministic pre-trade risk checks (stop-loss, volatility limits, exposure caps) ensuring live execution remains safe, explainable, and compliant with user authorization.Financial & Strategy Evals: Build rigorous evaluation harnesses to benchmark agent-generated strategies for code correctness, financial logic, and backtesting validity.Reference Strategy Library: Build, backtest, and maintain a core catalog of benchmark trading strategies to serve as modular templates and demonstrate agent workflows.RequirementsPursuing degree in Quantitative Finance, Financial Engineering (MFE), Computer Science, Applied Math, Statistics, or related STEM fields.Solid grasp of systematic trading concepts: alpha signals, momentum, mean-reversion, factor models, slippage, and transaction costs.Proficient in Python quant libraries: pandas, numpy, and backtesting frameworksPrior projects, research, or internships building with LLMs (tool/function calling, structured outputs, RAG, or agent frameworks).A systematic mindset that bridges probabilistic LLMs with deterministic financial math and market mechanics.Amber Group opens its doors to the curious problem solver empowered to make an impact in shaping tomorrow. As a hyper-growth company since day 1, we continually invite talent to join our diverse, nimble and digitally-native teams. If this sounds like you, apply now, or get in touch with us today at