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AI Product Security - AppSec - Assistant Manager

Grant Thornton INDUS -
Kolkata, West Bengal

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Job details

Qualifications

CI/CD
Azure
Law
Enterprise Software
DevOps
Master's degree
AWS
Machine learning
NIST standards
Continuous integration
Azure Certification
AI
RMF
AWS Certified Security – Specialty
SDLC
Design patterns

Full job description

Job ID: 865218

7 - 9 Years

1 Opening
Bengaluru, Kolkata

Role description

Role Overview

We are looking for a senior security leader to define and scale end-to-end Product Security across modern cloud-native and AI-driven systems.

You will own security across the full lifecycle—from secure design and threat modeling, to DevSecOps pipeline security, to AI/LLM security governance, to vulnerability management and PSIRT operations.

This is a hands-on leadership role requiring deep technical expertise and the ability to influence engineering teams at scale while enabling fast, secure product delivery.

What You Will Own (Outcomes)

1. Secure-by-Design Engineering

Define and enforce Secure SDLC standards across product engineering teams
Lead architecture-level security reviews for high-risk systems and features
Drive threat modeling (STRIDE / MITRE ATT&CK)
Establish reusable secure design patterns (identity, secrets, crypto, data protection)

2. DevSecOps at Scale

Embed security controls into CI/CD pipelines (shift-left + shift-right)
Operationalize SAST / SCA / Secrets scanning / IaC security
Implement DAST and runtime security validation
Drive SBOM generation, artifact signing, and provenance controls
Define release security gates and remediation SLAs
deploy): SAST, SCA, secret scanning, IaC/K8s policy-as-code, SBOM generation, artifact signing and provenance.
Operationalize DAST via Veracode integration patterns and developer runbooks; track fix SLAs, break-glass criteria, and remediation metrics.
Partner with Cloud & Platform teams to ensure telemetry, detection, and incident hooks align with SOC/SIEM runbooks.

3. AI / LLM & Data Security

Define and implement AI/ML and LLM security controls
Secure AI lifecycle: training, inference, deployment
Mitigate prompt injection, data leakage, and model abuse risks
Enforce data protection via DLP frameworks (e.g., Microsoft Purview)
Establish AI governance, lineage, and monitoring .
Engineer AI security guardrails: prompt/input validation, output filtering, model abuse monitoring, adversarial testing (prompt injection, data exfiltration, hallucination risk), dataset/model lineage, and access controls.
Integrate AI security tests into CI/CD pipelines and enforce Microsoft Purview DLP policies to prevent data leakage in AI-assisted development.

4. Product Security Incident Response (PSIRT)

Lead vulnerability intake, triage, and coordinated disclosure
Drive patching, remediation tracking, and customer communication
Align PSIRT with supply chain and GRC frameworks
Track KPIs (MTTR, vuln aging, exploitability, SBOM coverage)

5. Security Leadership & Metrics

Define product security metrics and reporting
Influence engineering leadership and drive adoption of standards
Act as a trusted advisor across Product, Engineering, and Security teams

Skills

Basic Qualifications

8+ years in Application Security / Product Security / Security Engineering
3+ years leading DevSecOps or AppSec programs
Strong experience with CI/CD security (Azure DevOps / similar)
Hands-on expertise in SAST, DAST, SCA, threat modeling
Experience securing cloud-native systems (AWS / Azure / GCP)

Preferred Qualifications

Experience in Product Security/AppSec roles at top-tier product companies
Experience building or scaling PSIRT programs
Familiarity with SBOM (SPDX / CycloneDX), SLSA, Sigstore, Cosign
Exposure to AI/ML or LLM security in production environments

AI/ML Security Certifications & Coursework (Preferred)

ISO/IEC 42001 Lead Implementer (AI governance and risk management for enterprise systems)
Certified AI Risk Manager (CAIRM) (AI risk identification and mitigation)
Training aligned to NIST AI Risk Management Framework (governance, risk, and compliance for AI systems)

Cloud AI & Security Certifications (Strong Practical Signal):

Microsoft Certified: Azure AI Engineer Associate
Microsoft Certified: Azure Security Engineer Associate
AWS Certified Machine Learning – Specialty
AWS Certified Security – Specialty

Nice to have these certifications but not mandatory or core for Product Security Manager more valuable for cloud security or AI/ML engineering roles.

About Grant Thornton INDUS

Grant Thornton INDUS is the global capability center for Grant Thornton US, the U.S. member firm of Grant Thornton International Ltd., a leading global network of independent audit, tax, and advisory firms. Founded in Chicago in 1924, Grant Thornton US is one of the leading accounting and advisory firms in the U.S., bringing together $4B+ in revenue, 56 U.S. offices, and a multi-national platform spanning 20 countries with 25,000 people. It combines deep expertise, advanced technology, and a collaborative mindset to help clients solve complex challenges and grow with confidence. Since 2012, Grant Thornton INDUS has brought together 3,300+ professionals across Tax, Audit, Advisory, Client Services, Innovation, and Enabling Functions to deliver high-impact solutions for Grant Thornton US and its global network. Recognized as a Great Place To Work® for three consecutive years and among India’s Top 15 Best Workplaces™ in Professional Services 2026, INDUS offers a high-performance culture where people are trusted, supported, and empowered to grow.

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cloud engineer devops jobs in wb

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Large Language Model Architect

Principal Solution Architect – Presales and AI

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.Net Programmer / Developer ( ASP.NET, MVC, C#, .Net Core )

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