AI Engineer-Cyber Security Transformation

Accountabilities: Design, develop, and operationalize AI-powered applications, copilots, and autonomous agents tailored to cybersecurity use cases and enterprise security requirements. Build retrieval-augmented generation (RAG) solutions that leverage enterprise knowledge repositories, security data, and contextual information to improve the accuracy and relevance of AI-generated insights. Develop integrations using the Model Context Protocol (MCP) and APIs to connect AI agents with security tools, enterprise platforms, and operational workflows. Engineer secure, scalable, and maintainable AI services using modern software engineering, DevOps, and deployment practices. Enhance self-hosted AI infrastructure, model-serving environments, and AI observability capabilities to support reliable enterprise-scale deployments. Develop and automate security workflows that improve analyst productivity, reduce manual effort, and streamline cybersecurity operations. Collaborate with security operations, risk, product security, vulnerability management, and threat intelligence teams to identify business needs and deliver practical AI-driven solutions. Implement and optimize agentic workflows and multi-agent systems to support complex security tasks and improve operational decision-making. Apply secure AI design principles to mitigate risks such as prompt injection, model misuse, sensitive data leakage, and unauthorized agent actions. Establish and maintain engineering standards for CI/CD, version control, automated testing, code quality, monitoring, and production readiness. Troubleshoot technical issues, evaluate emerging AI technologies, and continuously improve the performance, security, scalability, and reliability of AI solutions. Requirements A bachelor's or master's degree in Computer Science, Artificial Intelligence, Software Engineering, Cybersecurity, Data Science, or a related technical discipline. At least five years of professional experience in software engineering, AI engineering, machine learning engineering, platform engineering, or a closely related field. Strong proficiency in Python and experience designing and developing API-driven architectures and production-grade AI applications. Hands-on experience applying large language models (LLMs), AI agents, prompt engineering, retrieval-augmented generation (RAG), vector databases, and semantic search. Demonstrated ability to build, deploy, and maintain AI-powered applications and services in production environments. Solid understanding of software engineering and DevOps practices, including CI/CD pipelines, version control, automated testing, and code quality management. Experience with self-hosted LLM environments, enterprise AI platforms, and model deployment or serving infrastructure. Practical knowledge of agentic workflows and multi-agent architectures, including the integration of AI agents with external tools and systems. Understanding of AI security risks, including prompt injection, model abuse, data leakage, and secure agent design, with the ability to implement appropriate safeguards. Strong analytical thinking, troubleshooting, and problem-solving skills, with the ability to translate complex technical challenges into effective solutions. Excellent communication and stakeholder management skills, with the ability to collaborate across multidisciplinary security and engineering teams. A proactive, detail-oriented mindset and a commitment to responsible AI development, continuous learning, and secure engineering practices. Additional qualifications that would be advantageous: Previous experience developing AI-powered solutions specifically for cybersecurity, security operations, threat intelligence, or vulnerability management. Experience integrating security tools and enterprise platforms through MCP or other API-based integration frameworks. Relevant professional certifications, such as Microsoft AI Engineer, Azure AI Engineer, AWS Machine Learning, CISSP, or comparable credentials. Benefits Flexible working environment: Benefit from a flexible work culture designed to support individual needs, well-being, and professional growth. Remote work opportunity: Work remotely from India, with the role associated with the Gurugram location and applicable location requirements. Professional development: Expand your expertise in artificial intelligence, machine learning, cybersecurity, and enterprise-scale technology solutions. Innovative technical environment: Work on advanced AI applications, intelligent agents, secure AI platforms, and cybersecurity automation initiatives. Cross-functional collaboration: Partner with specialists across security, engineering, risk, and threat intelligence to solve complex technical challenges. Employee well-being: Join a workplace that emphasizes employee support, personal growth, recognition, and work-life balance. Inclusive workplace culture: Be part of an environment that values diversity, respects individual perspectives, and promotes equal opportunity. Meaningful technical impact: Contribute to secure and responsible AI adoption while helping improve cybersecurity capabilities and operational efficiency across the organization.