AI Security Engineer Industrial AI & Cybersecurity

Company: JK Cement

Function: Information Security & ISMS

Reports to: Head of Cybersecurity & ISMS

Location: Gurugram, Periodic travel to plant sites required Employment type: Full-time

Experience: 24 years in cybersecurity, AI/ML security, application security, cloud security, OT security, or related security roles. Exposure to AI/ML security or industrial/OT environments will be preferred.

Education: BE / B.Tech in Computer Science, Information Technology, Cybersecurity, Artificial Intelligence, Data Science, Electronics & Communication, Instrumentation, Automation, or related engineering discipline (minimum)

About the Role

JK Cement is scaling Artificial Intelligence across both its manufacturing operations and its enterprise. Our private Large Language Model, AI-enabled Central Control Room (CCR) systems, predictive maintenance models, and integrations with SAP, Salesforce, and other business platforms are helping our teams run plants more reliably, safely, and eWiciently.

The role will focus on securing AI-enabled decision-support systems and enterprise AI integrations, while ensuring that manufacturing safety, human oversight, and operational

reliability remain central to every deployment.

As that footprint grows, so does the attack surface and the stakes. A compromised model or pipeline here doesn't just risk data; it can aWect kiln stability, equipment reliability, and operational safety.

We're hiring an AI Security Engineer to secure this new generation of AI-driven systems end to end: from the SCADA, PLC, and historian layer in the plant, up through the model registries and inference environments, to the LLM prompts, APIs, and enterprise connectors that business teams rely on. This is a role for someone who is genuinely excited by the meeting point of AI/ML security and operational technology (OT) and who wants to do it in real industrial environments, not lab scenarios.

What You'll Do

- Design and implement security controls for AI and LLM-based systems across manufacturing, CCR operations, SAP, Salesforce, and other enterprise applications.




- Secure the full AI surface: model access, prompt flows, APIs, connectors, and data pipelines that power CCR decision-support and process-optimization use cases.
- Assess and mitigate AI-specific threats prompt injection, model poisoning, adversarial attacks, data leakage, model theft, and unauthorized model usage using frameworks such as the OWASP Top 10 for LLM Applications and MITRE ATLAS.
- Partner with manufacturing, IT, OT, and data science teams to secure AI systems that connect to SCADA, PLCs, IoT sensors, historians, and operational data platforms.
- Review and harden ML pipelines, model registries, training datasets, inference environments, and MLOps tooling (e.g., MLflow, Kubernetes, Docker, PyTorch, Hugging Face).
- Define and monitor AI security guardrails: role-based access, data loss prevention, model-usage monitoring, logging, and anomaly detection.
- Support and coordinate AI red-teaming exercises, security testing, compliance reviews, and secure deployment of AI use cases.
- Translate findings into clear, prioritized guidance for plant teams, developers, data scientists, and leadership.
- Maintain AI security documentation, risk registers, security review records, exceptions, control evidence, and governance trackers to support ISMS, audit, compliance, and secure AI adoption requirements.

What Success Looks Like

In the first 90 days, you'll have mapped the AI and data flows across our priority use cases, identified the highest-consequence risks, and proposed a prioritized remediation plan.

Within the first year,



you'll have established repeatable security guardrails and review processes that let teams ship new AI use cases quickly and safely making security an enabler of our Industry 4.0 roadmap rather than a bottleneck.

What You'll Bring (Must-Have)

- 24 years across cybersecurity, AI/ML security, cloud security, application security, or OT security (a robust mix of two or more is ideal).
- Practical understanding of AI/ML systems and the model lifecycle including LLMs, APIs, data pipelines, and secure software development practices.
- Hands-on familiarity with AI security risks: prompt injection, model poisoning, adversarial ML, sensitive-data exposure, and insecure model deployment.
- Working knowledge of relevant tooling e.g., MLflow, PyTorch, TensorFlow, Hugging Face, Kubernetes, Docker, GitHub, CI/CD pipelines, or cloud-native security tools.
- Strong communication skills and the ability to work credibly with plant teams, data scientists, developers, infrastructure teams, and security stakeholders.

Nice-to-Have

- Exposure to enterprise applications and integrations especially SAP, Salesforce, API gateways, and identity platforms.
- Familiarity with manufacturing or OT environments: SCADA, PLCs, IoT sensors, industrial networks, or process-control systems.
- Experience with data-protection controls and DLP.
- Relevant certifications (e.g., security, cloud, or OT/ICS credentials) are a plus, not a requirement.

Don't tick every box? If you're strong in AI/ML security or in OT security and motivated to grow into the other, we'd still like to hear from you.

Why You'll Love It Here

- You'll tackle meaningful AI security challenges in real manufacturing environments — work with direct operational impact.
- You'll help shape secure AI adoption across plants, enterprise systems, and our broader Industry 4.0 initiatives.
- You'll collaborate with passionate teams spanning cybersecurity, manufacturing, data science, IT, and operations.
- You'll grow through dedicated AI security programs, Industry 4.0 projects, cybersecurity forums, and conferences.
- You'll join a culture that values innovation, safety, operational excellence, sustainability, and responsible technology.

📌 AI Security Engineer For Industrial AI & Cybersecurity (Gurugram)
🏢 JK Cement
📍 Gurugram