AI Security Architect

Top Gen AI Jobs

Hyderabad

Hybrid

INR 5,236,000 - 6,607,000

Full time

4 days ago

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Benefits offered by this job

Hybrid work model

Job summary

Alter Domus is hiring an AI Security Architect to design and govern secure AI use across the enterprise. The role blends cybersecurity architecture with AI/ML security, observability, and governance in a hybrid Hyderabad setting.

The position requires 7+ years in cybersecurity architecture, plus 2+ years of hands-on AI/ML development experience, and familiarity with cloud platforms (AWS, Azure, GCP). Hybrid work model in Hyderabad, India is offered.

Qualifications

7+ years in cybersecurity architecture or engineering roles.
2+ years of hands-on AI/ML development experience.
Experience working in AI/ML or data engineering environments.
Experience designing observability and structured logging solutions for AI/ML systems.
Experience with cloud security platforms and AI services across AWS, Azure, and/or GCP.

Responsibilities

Design secure-by-design architecture guidelines for AI/ML platforms across ingestion, training, deployment, and inference.
Define reference security architectures, patterns, and guardrails for secure AI development.
Design risk-based AI security controls for regulatory and enterprise requirements.
Partner with engineering teams to automate and embed security guardrails into AI pipelines and toolchains.
Create and maintain guardrails for integrating AI security tools with enterprise infrastructure.
Analyze and build security requirements for AI-powered solutions at enterprise scale.
Architect MCP gateway integrations to prevent unauthorized tool invocation and data leakage.
Define policies for MCP server authentication, authorization scopes, and least-privilege access.
Implement rate limiting, input/output filtering, content inspection, and sandboxing for MCP-enabled workflows.
Evaluate third-party MCP plugins and tools for security risks before deployment.
Collaborate with platform and AI engineering teams to operationalize MCP guardrails across environments.
Evaluate AI tools and ecosystems including OpenAI, Claude, and Cursor.
Understand model architectures, prompt engineering, and security implications of deployment.
Lead AI-specific risk assessments and security design reviews.
Develop adversarial testing frameworks and work with red teams to validate resilience.
Stay current with emerging AI security threats, research, and defensive techniques.
Present findings to technical and executive stakeholders.
Establish security policies for ethical and responsible AI use.
Ensure compliance with NIST AI RMF, ISO 42001, GDPR, HIPAA, PCI-DSS, and SOC 2.
Collaborate with IT, data engineering, and product teams to embed security into AI development lifecycles.
Lead cross-functional projects to integrate AI security controls across business units.
Develop metrics and KPIs to measure effectiveness of the AI security program.

Skills

LLM Security

Gen AI

LangChain

LlamaIndex

OpenAI

Claude

Prompt Injection

Adversarial ML

AI Red Teaming

Python

TensorFlow

PyTorch

Pandas

Scikit-learn

NumPy

Tools

AWS

Azure

GCP

Job description

Description

Alter Domus is hiring an AI Security Architect to design and govern secure AI use across the enterprise. The role combines cybersecurity architecture, AI/ML security, observability, and governance in a hybrid Hyderabad setup.

Home/Jobs/AI Security Architect

AI Security Architect

Alter Domus

Hyderabad

7+ years

1 day ago

$55.4K–69.9K/yr

Full-time

Hybrid

Skills Required

LLM Security
Gen AI
LangChain
LlamaIndex
OpenAI
Claude
Prompt Injection
Adversarial Machine Learning
AI Red Teaming
Python
TensorFlow
PyTorch
Pandas
Scikit-learn
NumPy

Company: Alter Domus

Role: AI Security Architect

Location: Hyderabad, India | Hybrid

Experience

7+ years in cybersecurity architecture or engineering roles
2+ years of hands-on AI/ML development experience
Experience working in AI/ML or data engineering environments
Experience designing observability and structured logging solutions for AI/ML systems
Experience with cloud security platforms and AI services across AWS, Azure, and/or GCP

Responsibilities

Design secure-by-design architecture guidelines for AI/ML platforms across ingestion, training, deployment, and inference
Define reference security architectures, patterns, and guardrails for secure AI development
Design risk-based AI security controls for regulatory and enterprise requirements
Partner with engineering teams to automate and embed security guardrails into AI pipelines and toolchains
Create and maintain guardrails for integrating AI security tools with enterprise infrastructure
Analyze and build security requirements for AI-powered solutions at enterprise scale
Design and enforce MCP security controls for agentic workflows, including tool allowlisting, trust boundaries, and prompt-level access controls
Architect MCP gateway integrations to prevent unauthorized tool invocation, privilege escalation, and sensitive data leakage
Define policies for MCP server authentication, authorization scopes, and least-privilege access
Implement rate limiting, input/output filtering, content inspection, and sandboxing for MCP-enabled workflows
Evaluate third-party MCP plugins and tools for security risks before deployment
Collaborate with platform and AI engineering teams to operationalize MCP guardrails across environments
Evaluate AI tools and ecosystems including OpenAI, Claude, and Cursor
Understand model architectures, prompt engineering, and security implications of model configuration and deployment
Work with vendors on AI security tool evaluation, procurement discussions, and implementation
Integrate AI capabilities into security analytics, dashboards, and workflow automation
Design observability frameworks for prompt/response logging, model telemetry, agent trails, and data pipeline audit logs
Develop detection use cases for prompt injection, jailbreaks, data exfiltration, anomalous agent behavior, and model drift
Build security dashboards and KPIs to measure AI security posture and surface risks to leadership
Establish feedback loops between detection findings and architecture controls
Identify and research AI threats such as model inversion, data poisoning, evasion, data leakage, prompt injection, and adversarial ML attacks
Lead AI-specific risk assessments and security design reviews
Develop adversarial testing frameworks and work with red teams to validate model resilience
Stay current with emerging AI security threats, research, and defensive techniques
Present findings to technical and executive stakeholders
Establish security policies for ethical and responsible AI use
Ensure compliance with NIST AI RMF, ISO 42001, GDPR, HIPAA, PCI-DSS, and SOC 2
Collaborate with IT, data engineering, and product teams to embed security into AI development lifecycles
Lead cross-functional projects to integrate AI security controls across business units
Develop metrics and KPIs to measure the effectiveness of the AI security programme and report outcomes to executive leadership

Additional Responsibilities

Support secure AI development while minimizing manual review friction
Build and maintain consistent enforcement of MCP guardrails across environments
Use cloud-native security monitoring tools for observability
Apply data science libraries and big data technologies in AI security work
Apply cybersecurity fundamentals including network security, endpoint protection, identity and access management, and threat hunting
Operate in ambiguous, fast-moving environments with strong analytical, problem-solving, and decision-making skills

Nice To Have

Familiarity with industry-specific requirements in financial services or healthcare
Support for professional accreditations such as ACCA and study leave
Flexible arrangements
Generous holidays
Additional day off for your birthday
Continuous mentoring
Active sports, events and social committees
24/7 support through the Employee Assistance Program
Opportunity to invest through the Employee Share Plan
Additional local benefits depending on location
Access to Alter Domus Academy learning zones and LinkedIn Learning resources

More Skills

cybersecurity architecture, AI/ML, prompt safety testing, generative AI governance, model inversion, data poisoning, evasion attacks, adversarial robustness testing, big data technologies, Model Context Protocol (MCP), MCP servers, MCP clients, tool invocation flows, MCP gateway configuration, guardrail implementation, access control policy design, multi-agent frameworks, tool-augmented LLM systems, identity scoped permissions, zero-trust, structured logging, cloud-native security monitoring tools, AWS, Azure, GCP, data protection, network security, endpoint protection, identity & access management, threat hunting, NIST AI RMF, ISO 42001, GDPR, HIPAA, PCI-DSS, SOC 2, financial services, healthcare

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