ISECURION
Website:
isecurion.com
Job details:
About the job
Company Description
ISECURION is a CERT-In empanelled and ISO 27001:2022 certified cybersecurity consulting company that helps organizations stay secure in an increasingly complex digital world. The team focuses on strengthening security posture, meeting compliance requirements, and building long-term cyber resilience for businesses of various sizes. Services include Vulnerability Assessment & Penetration Testing (VAPT), compliance audits, cloud security, DFIR, risk assessments, and managed security services. ISECURION is known for its practical, business-focused approach that goes beyond identifying vulnerabilities to explaining impact, prioritizing remediation, and aligning with industry standards and regulations. The company is driven by a passionate team committed to research, innovation, and delivering meaningful security outcomes.
Role Description
We are looking for a motivated AI/ML Engineer with 1–2 years of experience to join our
product engineering team. The candidate will work on building and integrating AI/ML
capabilities into cybersecurity products, with a strong focus on automation, intelligent
analysis, test-case generation, security workflows, and AI-driven content generation.
The ideal candidate should have strong programming skills in Python, a good understanding of
AI/ML algorithms and concepts, and the ability to independently understand requirements,
design solutions, create test cases, and implement working prototypes.
The candidate should also be comfortable working with cybersecurity concepts and modern AI
integration technologies such as LLMs, agentic workflows, tool calling, MCP (Model Context
Protocol), and AI orchestration frameworks.
Key Responsibilities:
- Design, develop, test, and deploy AI/ML-based features for cybersecurity applications.
- Build intelligent systems capable of analyzing security-related data and generating meaningful outputs.
- Develop AI-based solutions for automated report, template, documentation, and content generation.
- Integrate Large Language Models (LLMs) with existing applications, APIs, tools, and security platforms.
- Work with MCP (Model Context Protocol) and similar technologies to connect AI models with external tools and services.
- Develop AI agents and automated workflows for executing multi-step tasks.
- Understand cybersecurity use cases and translate security requirements into AI/ML solutions.
- Research and evaluate different AI/ML approaches to solve practical product problems.
- Develop prompts, structured outputs, evaluation mechanisms, and guardrails for LLM- based applications.
- Evaluate AI-generated results and continuously improve model performance and output quality.
- Implement appropriate algorithms and techniques for classification, prediction, text processing, information extraction, and other ML use cases.
- Work closely with software developers, cybersecurity engineers, QA engineers, and product teams.
- Stay updated with emerging developments in AI, ML, Generative AI, LLMs, AI agents,
and cybersecurity.
Skills & Qualifications:
- Strong knowledge of Python, including writing clean, modular, maintainable, and testable code.
- Knowledge of common ML techniques such as classification, regression, clustering, decision trees, and basic neural networks.
- Good understanding of Generative AI, LLMs, prompt engineering, structured outputs, embeddings, RAG, tool/function calling, and AI agents.
- Experience working with LLM APIs and integrating AI models with applications, REST APIs, databases, and external tools.
- Understanding of MCP (Model Context Protocol) and AI-driven automation or willingness to learn and implement it.
- Ability to design and build multi-step AI workflows and automation pipelines.
- Good understanding of LLM limitations, including hallucinations, context limitations, and inconsistent outputs, with the ability to design reliable AI workflows.
- Ability to understand cybersecurity requirements and translate them into practical AI/ML solutions.
- Strong knowledge of data structures, algorithms, problem-solving, and analytical thinking.
- Ability to independently create test cases, identify edge cases, evaluate AI-generated results, and troubleshoot unexpected outputs.
- Familiarity with vector databases, Docker, Git, CI/CD, and cloud platforms is an advantage.
- Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Information Technology, Cybersecurity, Data Science, or a related technical field.
- 1–2 years of relevant experience in AI/ML, Generative AI, software development, or a
related field.
Click on Apply to know more.
