Lead Security Engineer - Data Security & RL for Cyberecurity

This role is for one of Weekday’s clients

Salary range: Rs 2500000 - Rs 6000000 (ie INR 25 - 60 LPA)

Min Experience: 3+ years

Location: Bangalore

JobType: full-time

We are seeking a highly skilled Lead Security Engineer - Data Security & Reinforcement Learning with 3-8 years of experience to design, implement, and strengthen security solutions across data-intensive and intelligent systems. This role combines strong Cybersecurity and Data Security expertise with practical knowledge of Reinforcement Learning (RL) and machine learning security.

The ideal candidate will be responsible for identifying security risks, protecting sensitive data, developing security controls, and exploring reinforcement learning techniques to improve threat detection, response, and security automation. You will work closely with engineering, data science, infrastructure, and security teams to build resilient systems that can securely operate at scale.

Requirements

Key Responsibilities

• Design and implement robust cybersecurity strategies, controls, and security architectures across applications, infrastructure, APIs, and data platforms.
• Develop and maintain data security controls covering data classification, encryption, access management, data protection, masking, tokenization, and secure data handling.
• Identify, assess, and mitigate security vulnerabilities, threats, and attack vectors across enterprise environments.
• Apply Reinforcement Learning and machine learning techniques to security use cases such as threat detection, anomaly detection, adaptive security controls, and automated incident response.
• Research and evaluate emerging approaches for using RL to improve cybersecurity decision-making and defensive automation.
• Develop security models and mechanisms capable of adapting to changing threats and attack patterns.
• Work with data science and ML teams to secure training data, models, pipelines, and inference environments.
• Protect sensitive datasets from unauthorized access, data leakage, poisoning, manipulation, and other security threats.
• Conduct security assessments, threat modeling, vulnerability analysis, and risk assessments for new and existing systems.
• Build monitoring and detection mechanisms to identify suspicious activities and potential security incidents.
• Support incident response, root-cause analysis, remediation, and implementation of preventive controls.
• Establish security best practices, technical standards, and engineering guidelines for data and ML systems.
• Lead security initiatives and mentor engineers while collaborating with cross-functional technical teams.

Must-Have Skills

• 3-8 years of professional experience in Cybersecurity, Information Security, Data Security, or related engineering roles.
• Strong hands-on expertise in Cybersecurity, including threat modeling, vulnerability management, security architecture, incident response, and security monitoring.
• Strong understanding of Data Security, including encryption, key management, access controls, data classification, DLP, IAM, and secure data processing.
• Practical knowledge of Reinforcement Learning, including RL concepts, agents, environments, rewards, policies, exploration/exploitation, and model training.
• Understanding of machine learning security risks, including adversarial attacks, data poisoning, model manipulation, and data leakage.
• Strong programming skills in Python or a comparable programming language.
• Experience with security tools, cloud security, APIs, databases, and modern distributed systems.
• Strong understanding of authentication, authorization, cryptography, network security, and secure software development practices.
• Ability to analyze complex security problems and translate them into scalable technical solutions.

Good-to-Have Skills

• Experience with AWS, Azure, or GCP security.
• Knowledge of ML frameworks such as PyTorch, TensorFlow, or similar platforms.
• Familiarity with SIEM, SOAR, EDR, IDS/IPS, and security analytics platforms.
• Knowledge of Kubernetes, containers, DevSecOps, and infrastructure-as-code security.
• Experience with LLM/AI security, autonomous security systems, or AI-driven threat detection.
• Familiarity with cybersecurity standards and frameworks such as NIST, ISO 27001, CIS, or MITRE ATT&CK.