HSBC Group

Some careers shine brighter than others.

If you’re looking for a career that will help you stand out, join HSBC and fulfil your potential. Whether you want a career that could take you to the top, or simply take you in an exciting new direction, HSBC offers opportunities, support and rewards that will take you further.

HSBC is one of the largest banking and financial services organisations in the world, with operations in 64 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and, ultimately, helping people to fulfil their hopes and realise their ambitions.

We are currently seeking an experienced professional to join our team in the role of Lead Security Engineer – Quantum Cryptography & AI Security

In this role, you will:

• Architect, develop, and deploy quantum-safe encryption schemes and protocols into existing systems. Integrate solutions based on cutting-edge post quantum algorithms.
• Evaluate emerging PQC algorithms and support the transition from conventional to quantum resistant cryptography in alignment with the NIST PQC standardization process.
• Collaborate with development teams to integrate quantum key distribution (QKD) protocols (e.g., BB84, E91, decoy state methods) and utilize quantum random number generators for high entropy key generation.
• Develop simulation and testing environments using quantum computing frameworks such as IBM Qiskit, Google Cirq, or Rigetti Forest, and implement cryptographic libraries (e.g., liboqs) for PQC algorithms.
• Conduct security reviews and penetration testing of AI/ML systems, with a particular focus on defending against adversarial attacks such as prompt injection, data poisoning, and model extraction.
• Collaborate with MLOps teams to integrate security best practices into the AI lifecycle—from data ingestion and model training to deployment and monitoring.
• Implement and evaluate adversarial machine learning techniques, including adversarial training, robust optimization, and the use of frameworks like CleverHans or Foolbox.
• Deploy tools for continuous monitoring of AI model performance (model drift, bias, and accuracy degradation) and utilize explainability methods (LIME, SHAP) to ensure transparency and security.
• Implement automated security testing (including static and dynamic analysis) within CI/CD pipelines for both traditional software and AI models.
• Promote secure coding practices across full stack development efforts and perform thorough code reviews.
• Conduct end to end penetration testing and threat modeling to ensure robust defenses against evolving attack vectors.

To be successful in this role, you should meet the following requirements:

• Minimum 5 years of hands on experience in information security engineering, with a strong focus on implementing quantum safe cryptography and securing AI/ML systems.
• Proven experience in secure coding, DevSecOps practices, penetration testing, and vulnerability assessments in highly regulated environments (preferably in the financial sector).
• Demonstrated track record in integrating advanced cryptographic solutions and defending AI systems against adversarial threats.
• Bachelor’s or Master’s degree in Computer Science, Cybersecurity, Electrical Engineering, or a related field.
• Industry certifications such as CISSP, CEH, OSCP, or equivalent.
• Specialized training or certifications in quantum cryptography (e.g., courses on post quantum cryptographic algorithms) and AI security (e.g., adversarial machine learning courses) are highly desirable.
• Deep Understanding of QKD Protocols: Expertise in designing and implementing quantum key distribution protocols (BB84, E91, decoy state, etc.).
• Proficiency in algorithms such as lattice based (e.g., NTRU, FrodoKEM), hash based, code based, and multivariate cryptography.
• Experience with quantum simulation platforms (IBM Qiskit, Google Cirq, Rigetti Forest) and cryptographic libraries (e.g., liboqs).
• Familiarity with quantum random number generators, quantum state preparation, and measurement techniques.
• Knowledge of the NIST PQC standardization process, including security proofs and algorithm performance evaluation.
• Advanced proficiency with TensorFlow, PyTorch, and scikit learn; strong Python programming skills.
• Experience implementing adversarial attack and defense techniques (e.g., FGSM, PGD, DeepFool) and integrating robust optimization in model training.
• Proven capability to perform comprehensive security assessments of AI systems, including static/dynamic analysis and threat modeling specific to AI/ML pipelines.
• Experience in identifying and mitigating vulnerabilities in large language models (LLMs), including prompt injection and data poisoning defenses.
• Familiarity with model explainability tools (LIME, SHAP) and continuous monitoring solutions for detecting model drift, bias, and performance degradation.
• Solid understanding of MLOps tools (Kubeflow, MLflow) and secure CI/CD pipeline practices for AI systems.

You’ll achieve more when you join HSBC.

www.hsbc.com/careers

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Issued by – HSBC Software Development India