Manager - Forward Deployed Engineer (FDE) - Risk Consulting

Position Overview

We are seeking a highly skilled and entrepreneurial AI Forward Deployed Engineer (Manager / Senior Manager level) to join our Risk Consulting team. This is a hybrid, high-impact role designed for a professional who possesses a unique combination of deep market/traded risk domain expertise, consulting acumen, and hands-on AI/ML engineering capabilities.

As a Forward Deployed Engineer, you will work directly on-site with leading financial institutions to design, prototype, and deploy production-grade AI, Generative AI (LLMs), and advanced analytics solutions to revolutionize their market risk, traded risk, and trading-floor operations.

Key Responsibilities

AI-Driven Risk Solutions: Lead the design, development, and deployment of AI/ML and Generative AI (LLM) solutions tailored for traded risk management, market risk frameworks, and trading systems.

Rapid Prototyping & Deployment: Act as a "forward-deployed" engineer, working closely with clients to build proof-of-concepts (PoCs) and rapidly scale them into production-grade risk engines.

Risk Framework Transformation: Evaluate clients' legacy risk management frameworks, trading strategies, and valuation systems to identify areas ripe for AI-driven automation, predictive modeling, and optimization.

Advanced Analytics & Stress Testing: Formulate and implement advanced machine learning models and stress-testing scenarios to quantify potential losses in trading portfolios (Rates, FX, Credit, Equities, Structured Products) stemming from major market shifts.

Automated Risk Reporting & Operations: Architect, automate, and manage the production of next-generation risk monitoring pipelines (daily PnL attribution, VaR fluctuations, limit monitoring) utilizing GenAI, advanced data engineering, and modern visualization tools.

Bridge Business & Tech: Act as the translation layer between client Front Office traders, Risk Management executives, and internal/external AI/Data engineering teams to implement and refine risk controls.

Regulatory & Industry Alignment: Stay abreast of industry trends, regulatory changes (e.g., FRTB), and emerging AI standards to ensure all deployed models are compliant, explainable (XAI), and robust.

Business Development & Thought Leadership: Contribute to business development by showcasing live demos, writing technical whitepapers on AI in Risk, and pitching innovative AI consulting solutions to senior client stakeholders.

Team Mentorship: Mentor and coach junior consultants and engineers, fostering a culture of continuous learning across quantitative finance and modern software engineering.

Qualifications & Experience

Education & Experience:

A bachelor’s or master’s degree in a highly quantitative field: Computer Science, Financial Engineering, Data Science, Mathematics, or Physics. A professional qualification such as CFA, FRM, or CQF is highly desirable.

6+ years of relevant experience spanning quantitative risk management, financial engineering, or machine learning engineering within global investment banks, top-tier securities houses, or leading consulting firms.

Technical Skills (Core FDE Requirements):

Programming & Frameworks: Exceptional proficiency in Python and standard machine learning libraries (scikit-learn, PyTorch, TensorFlow). Strong SQL and database management skills are required.

Generative AI & LLMs: Hands-on experience with LLMs, prompt engineering, Retrieval-Augmented Generation (RAG) frameworks (e.g., LangChain, LlamaIndex), and vector databases.

Data & MLOps: Experience with data pipelines (ETL), cloud platforms (AWS, Azure, or GCP), and DevOps/MLOps practices (Git, Docker, CI/CD) for deploying models in secure enterprise environments.

Risk Domain Knowledge:

Strong understanding of Market Risk and Traded Risk frameworks, including VaR, Expected Shortfall (ES), Stress Testing, Sensitivity Analysis, and regulatory standards (e.g., FRTB).

Solid knowledge of financial products (FICC, equities, derivatives, complex structured products) and related pricing/valuation methodologies.

Exposure to Counterparty Credit Risk, XVA, Liquidity Risk, or ALM/IRRBB is a significant plus.

Consulting & Leadership Skills:

Proven experience in managing complex technical projects with multiple senior stakeholders.

Excellent problem-solving skills, with a track record of transforming ambiguous business problems into structured technical solutions.

Superb communication and presentation skills, with the ability to explain complex AI/ML concepts to non-technical, C-suite executives.

Fluency in English and Mandarin is essential for client engagement in Hong Kong and the wider Asia-Pacific region.