AI Engineer – Cyber Security Transformation
New
J
JobgetherCybersecurity AI
Work remotely from IndiaFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- At least five years of professional experience in software engineering, AI engineering, machine learning engineering, platform engineering, or a closely related field.
- Required Skills
- PythonCI/CDPrompt EngineeringLLM
Requirements
- 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 API-driven architectures and production-grade AI applications.
- Hands-on experience with large language models, AI agents, prompt engineering, retrieval-augmented generation, vector databases, and semantic search.
- Experience building, deploying, and maintaining AI-powered applications and services in production.
- Knowledge of 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, multi-agent architectures, and integrating AI agents with external tools and systems.
- Understanding of AI security risks, including prompt injection, model abuse, data leakage, and secure agent design.
- Additional qualifications include cybersecurity AI experience, security-tool integrations through MCP or APIs, and relevant AI, cloud, or cybersecurity certifications.
Responsibilities
- Design, develop, and operationalize AI-powered applications, copilots, and autonomous agents for cybersecurity use cases.
- Build retrieval-augmented generation solutions using enterprise knowledge repositories, security data, and contextual information.
- Develop MCP and API integrations connecting AI agents with security tools, enterprise platforms, and operational workflows.
- Engineer secure, scalable, and maintainable AI services using software engineering, DevOps, and deployment practices.
- Enhance self-hosted AI infrastructure, model-serving environments, and AI observability capabilities.
- Develop and automate workflows to improve analyst productivity and streamline cybersecurity operations.
- Collaborate with security operations, risk, product security, vulnerability management, and threat intelligence teams.
- Implement agentic workflows and multi-agent systems for complex security tasks.
- Apply secure AI design principles to address prompt injection, model misuse, sensitive data leakage, and unauthorized agent actions.
- Establish engineering standards for CI/CD, version control, testing, code quality, monitoring, and production readiness.
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