Company Description :

- Are you looking to join an organization that is growing and dynamic? What about a high-energy, collaborative environment that rewards hard work? **

J.S. Held is a global consulting firm that combines technical, scientific, financial, and strategic expertise to advise clients seeking to realize value and mitigate risk. Our professionals serve as trusted advisors to organizations facing high stakes matters demanding urgent attention, staunch integrity, proven experience, clear-cut analysis, and an understanding of both tangible and intangible assets.

The firm provides a comprehensive suite of services, products, and data that enables clients to navigate complex, contentious, and often catastrophic situations.

J.S. Held, a global consulting firm providing specialized technical, scientific, financial, and advisory services, is seeking an AI Security Engineer is a senior, hands‑on technical role responsible for designing, engineering, and operationalizing AI security across J.S. Held’s enterprise.

The role balances hands‑on engineering, solution design, and architectural leadership. While expected to influence standards, patterns, and roadmaps, this is not a purely strategic role—the engineer will actively design and enable controls.

Role weighting:

- ~70% AI Security Engineering (primary)
- ~30% Data Security Engineering (secondary), with emphasis on Microsoft Purview, especially where enterprise data is used by AI systems.

Core Responsibilities

AI Security Engineering (Primary - ~70%)

AI Security Architecture & Guardrails

- Define and evolve the enterprise AI Security Architecture, guardrails, and security requirements aligned to business objectives.
- Establish secure‑by‑design patterns across AI development, deployment, and operations, including requirements for hardening, hosting,



access control, monitoring, and testing.

Platform & Engineering Enablement (Hands‑On)

- Design and engineer security controls for:

- Internal AI agents and automation workflows

- Model hosting, inference services, APIs, and orchestration layers

- RAG architectures, vector databases, and embeddings

- Model training and fine‑tuning pipelines

- MCP and agent‑to‑agent interaction patterns

AI Identity, Authentication & Authorization

- Extend identity and access principles to non‑human identities and autonomous agents.
- Treat AI agents as first‑class identities, defining authentication, authorization, lifecycle management, and revocation.
- Implement delegated and “on‑behalf‑of” authorization patterns to distinguish human‑initiated actions from agent‑initiated actions.

Threat Modeling & Risk Reduction

- Identify and mitigate AI‑specific risks including data leakage, prompt injection, jailbreaks, model abuse, data poisoning, model extraction, and AI supply‑chain risk.
- Ensure appropriate security testing and validation is embedded into AI development and deployment workflows.

Monitoring & Incident Readiness

- Define logging, monitoring, and detection requirements for AI systems, models, and agent activity.
- Partner with SecOps to ensure AI‑related events are observable, auditable, and actionable.
- Support incident response and post‑incident analysis for AI‑related security events.





Cross‑Functional Delivery

- Work closely with IAM, SecOps, AppSec, GRC, IT engineering, AI platform teams, and business stakeholders to embed security controls where they belong.

Data Security Engineering (Secondary - ~30%)

Data Protection & Governance

- Design and enhance enterprise data security controls with a focus on AI‑driven data access.
- Implement and optimize Microsoft Purview, including data classification, sensitivity labeling, DLP, information protection, and visibility.

AI‑Aware Data Security

- Ensure data security controls are aligned to AI architectures, reducing risk of sensitive data exposure via prompts, agents, outputs, and downstream sharing.
- Support secure use of enterprise data in RAG pipelines, AI workflows, and training environments.

Multi‑Platform Data Flows

- Contribute to data protection strategies across collaboration platforms, cloud services, and endpoints, ensuring consistent enforcement where possible.

Qualifications

Required Qualifications

- This role requires high proficiency in English (verbal and written) due to regular interaction with global stakeholders. It also requires an excellent Wi‑Fi connection with stable internet.
- Schedule aligned with UK business hours. This usually means working from around 2:00 PM to 11:00 PM IST, to match the 8:30 AM to 5:30 PM GMT workday in the UK.
- Direct, hands‑on experience with Azure AI Foundry and Copilot Studio in enterprise environments
- Solid experience securing cloud and SaaS platforms (Azure preferred)
- Proven ability to translate security requirements into practical, deployable controls

Preferred Qualifications

- Experience securing generative AI, LLM‑based systems, and agentic architectures
- Exp

📌 Ai Security Engineer (Mumbai)
🏢 J.S. Held
📍 Mumbai