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Job Description – Information Security Engineer (Generalist – AI & Automation Focus)

About Us:

Atlas Systems Inc. is a Software Solutions company headquartered in East Brunswick, NJ.Incorporated in 2003, Atlas provides solutions in GRC, Technology, Procurement, Healthcare Provider and Oracle to customers across the globe.

For more information, please visit our website: https://www.atlassystems.com/

Please click on the link below to apply for this position:
https://atlas.bamboohr.com/careers/609

Job Title: Information Security Engineer (Generalist – AI & Automation Focus)
Location: Bangalore / Chennai (Onsite / Hybrid)
Work Timing: IST Hours
Experience: 5–10 Years (Flexible based on skill fit)
Employment Type: Full-Time

Position Summary

We are seeking a hands-on Information Security Engineer (Generalist) to support daily security operations and security initiatives across monitoring, incident response, vulnerability management, IAM, data protection, application/cloud security, compliance, and automation.

A key focus of this role is securing enterprise adoption of Generative AI, LLMs, AI agents, bots, copilots, automation, and AI-assisted software development. The engineer will help establish practical information, data, application, and AI security controls that enable responsible AI adoption while protecting sensitive information, customer trust, and regulatory obligations.

Experience in financial services, capital markets, Partner Capital, fintech, or other regulated environments is highly desirable.

Key Responsibilities

Security Operations & Incident Response

• Perform security monitoring, alert triage, investigation, escalation, and incident response.
• Support and manage security platforms including SIEM, EDR/XDR, IAM, DLP, vulnerability management, endpoint and cloud security tools.
• Maintain security runbooks, detection/response processes, dashboards, and operational metrics.

Vulnerability, Risk & Compliance

• Drive vulnerability assessment, prioritization, remediation tracking, and validation across applications, infrastructure, endpoints, and cloud.
• Support security risk assessments, control-gap analysis, audit evidence, compliance activities, and security documentation.
• Coordinate remediation with Engineering, DevOps, IT, Cloud, Data, Risk, and Compliance teams.

AI Security & Governance

• Support security governance for GenAI, LLMs, AI agents, bots, copilots, AI APIs, and AI-enabled development tools.
• Assess AI risks including prompt injection, sensitive-data exposure, insecure AI-generated code, excessive agent permissions, unsafe tool invocation, secrets exposure, and insecure integrations.
• Establish controls for approved AI services, identity and least privilege, data classification, API security, logging, monitoring, auditability, retention, and human oversight.
• Review AI applications, agents, automation workflows, and AI-assisted code as part of security architecture and secure SDLC.

Application, Data, Cloud & Identity Security

• Support secure SDLC practices including threat modeling, API security, SAST/DAST/SCA, secrets scanning, and application security reviews.
• Protect sensitive and regulated data through classification, DLP, encryption, access controls, and secure data handling.
• Support IAM, MFA, privileged access, service identities, secrets management, cloud security, and least-privilege controls, particularly for AI agents and automation accounts.

AI development, Security Automation & Collaboration

• Automate security operations, investigation, reporting, evidence collection, and remediation using Python, PowerShell, APIs, SOAR/workflows, and AI-assisted tools.
• Partner with Engineering, DevOps, Cloud, IT, Data, Risk, Compliance, and business teams to resolve security issues and enable secure technology adoption.
• Capability to develop specific AI embedded agents / bots / applications that can solve specific use cases like Data Loss Prevention (DLP), Pishing queue triage, Due diligence questionnaires etc.

Required Qualifications

• Bachelor's/master's degree in computer science, Cybersecurity, Information Security, Engineering, or related discipline.
• 5–10 years of cybersecurity engineering, information security operations, or related experience with broad security-domain exposure.
• Hands-on experience with SIEM, EDR/XDR, IAM, DLP, vulnerability management, or comparable enterprise security technologies.
• Experience in incident investigation, vulnerability remediation, risk management, and compliance/audit support.
• Experience with AI agent / Bot development, Python, PowerShell, REST APIs, SOAR, workflow automation, or equivalent scripting technologies.
• Exposure to Generative AI, LLMs, AI agents, AI-assisted development, or AI security/governance.
• Strong understanding of least privilege, secure SDLC, data protection, application/cloud security, and risk management.
• Strong problem-solving, documentation, communication, and cross-functional collaboration skills.
Financial services, capital markets, Partner Capital, fintech, or regulated-industry experience is preferred.

Technical Skills

Security Operations: SIEM, EDR/XDR, SOC operations, threat detection, incident response, log analysis.

Identity & Data Security: IAM, RBAC, MFA, privileged access, secrets management, DLP, encryption, data classification.

Application & Cloud Security: Secure SDLC, SAST/DAST/SCA, API security, threat modeling, cloud security and configuration management.

AI Security & Governance: GenAI/LLMs, AI agents, prompt/instruction security, AI data governance, agent permissions, AI application security, logging and auditability.

AI development, Automation & Risk: AI agent / bot development skills, Python, PowerShell, REST APIs, SOAR/workflows, security automation, risk assessment and compliance.

Core Competencies

• Security Operations & Incident Response
• AI Security & Governance
• Application, Data & Cloud Security
• Identity & Access Management
• Vulnerability & Risk Remediation
• Security Automation & Process Optimization
• Security Compliance & Audit Readiness
• Cross-Functional Collaboration & Problem Solving

Success Measures

• Effective security monitoring, investigation, incident response, and timely remediation.
• Reduced vulnerability, identity, application, cloud, and data-security exposure.
• Effective governance and risk reduction for enterprise AI, agents, bots, copilots, and AI-assisted software development.
• Protection of sensitive, customer, proprietary, and regulated information from unauthorized AI or application exposure.
• Improved security operations efficiency through automation and AI-assisted capabilities.
• Strong audit readiness, security documentation, compliance posture, and timely closure of security findings.