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AI Security Architect

Alter Domus

Hyderabad

7+ years

Today

$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

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.

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 solid 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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