AppSec & AI Security Manager

Alignity Solutions

Job Location:

Hyderabad - India

Salary: Not Disclosed

Experience Required: 8years

Posted on: 2 days ago

Vacancies: 1 Vacancy

Job Summary

Do you love a career where you Experience Grow & Contribute at the same time while earning at least 10% above the market If so we are excited to have bumped onto you.
Learn how we are redefining the meaning of work and be a part of the team raved by Clients Job-seekers and Employees.
Jobseeker Video Testimonials
Employee Glassdoor Reviews
If you are a AppSec & AI Security Manager with 8 Yrs looking for excitement challenge and stability in your work then you would be glad to come across this page.
We are an IT Solutions Integrator/Consulting Firm helping our clients hire the right professional for an exciting long-term project. Here are a few details.
Check if you are up for maximizing your earning/growth potential leveraging our Disruptive Talent Solution.
Role: AppSec & AI Security Manager
Location: Hyderabad BanagaloreChennaiPuneGurgaon/New DelhiKolkataMumbai
Experience: 8 to 12 years
Position Summary
We are seeking an AppSec & AI Security Architect to lead and deliver security architecture
reviews and secure-by-design outcomes across modern applications cloud-native platforms
APIs third-party integrations and AI-enabled systems. This role combines deep technical
expertise with delivery leadershipoverseeing teams and engaging senior client stakeholders.
For LLM RAG copilot bot and agentic systems you will evaluate and mitigate risks such as
prompt injection sensitive data disclosure insecure tool/function calling excessive
agency/permissions insecure output handling model and dependency supply-chain risks
training/fine-tuning data leakage and vector database/embedding store weaknesses and
drive adoption of practical guardrails and governance.
As an AppSec & AI Security Manager you will:
Architect and oversee the build of AI agents and agentic workflows for security
automation (e.g. AppSec triage agents security copilots autonomous remediation
workflows AI red-team automation).
Lead end-to-end delivery of AppSec DevSecOps and AI Security (AISecOps)
engagementsmanaging onshore/offshore engineers and architects across the lifecycle
(assess design implement operate).
Define and drive adoption of secure-by-design architectures for modern applications
cloud-native platforms and AI/agentic systems; establish reference architectures and
reusable patterns.
Review and approve security architecture for systems spanning microservices APIs
distributed platforms and AI/RAG/agentic solutions including data flows trust
boundaries secrets encryption and third-party dependencies.
Establish reusable patterns for CI/CD pipeline security policy-as-code IaC scanning
and software/artifact integrity (e.g. SBOM and ML-BOM workflows) aligned to secure
SDLC goals.
Establish and assess container/Kubernetes security patterns (admission control multi-
tenant isolation runtime protection) and supply-chain controls (e.g. SLSA sigstore).
Define and assess LLM/agent guardrails (prompt/output handling controls grounding
strategies tool allow-listing sandboxing rate limits/quotas and human-in-the-loop
patterns) and verify effectiveness through testing.
Drive LLM/agent security testing (abuse/misuse cases prompt injection/jailbreak
testing tool-use abuse validation adversarial evaluation) and ensure findings are
translated into actionable mitigations and risk decisions.
Define runtime monitoring and incident response requirements for AI systems (secure
telemetry privacy-aware prompt/output logging patterns abuse detection drift signals
containment/rollback playbooks).
Shape clients enterprise AppSec and AISecOps programsbuild roadmaps aligning
security investment with business outcomes and regulatory requirements; define
governance metrics and operating model.
Serve as the primary day-to-day client interfacebuild rapport and trust with senior
stakeholders (e.g. CISOs CTOs Heads of AI/Engineering) and guide prioritization and
decision-making.
Oversee the quality of project deliverablesassessment reports architectures threat
models runbooks and risk/security recommendations.
Support business development: define scope build estimates and pricing package
proposals and support proposal presentations.
Contribute to eminencewhitepapers points-of-view conference contenton the
convergence of AppSec DevSecOps and AISecOps.
Lead talent processesrecruiting coaching performance management and capability
building for AppSec and AI Security professionals.

Requirements

Qualifications
Must-have skills / project experience / certifications (AI Security Focus)
6 years of progressively responsible experience in application security DevSecOps
product security and/or security architecture with increasing scope and ownership;
including 2 years in consulting project leadership or client-facing delivery.
Strong knowledge of
Required Skills:
Position Summary We are seeking an AppSec & AI Security Architect to lead and deliver security architecture reviews and secure-by-design outcomes across modern applications cloud-native platforms APIs third-party integrations and AI-enabled systems. This role combines deep technical expertise with delivery leadershipoverseeing teams and engaging senior client stakeholders. For LLM RAG copilot bot and agentic systems you will evaluate and mitigate risks such as prompt injection sensitive data disclosure insecure tool/function calling excessive agency/permissions insecure output handling model and dependency supply-chain risks training/fine-tuning data leakage and vector database/embedding store weaknesses and drive adoption of practical guardrails and governance. As an AppSec & AI Security Manager you will: Architect and oversee the build of AI agents and agentic workflows for security automation (e.g. AppSec triage agents security copilots autonomous remediation workflows AI red-team automation). Lead end-to-end delivery of AppSec DevSecOps and AI Security (AISecOps) engagementsmanaging onshore/offshore engineers and architects across the lifecycle (assess design implement operate). Define and drive adoption of secure-by-design architectures for modern applications cloud-native platforms and AI/agentic systems; establish reference architectures and reusable patterns. Review and approve security architecture for systems spanning microservices APIs distributed platforms and AI/RAG/agentic solutions including data flows trust boundaries secrets encryption and third-party dependencies. Establish reusable patterns for CI/CD pipeline security policy-as-code IaC scanning and software/artifact integrity (e.g. SBOM and ML-BOM workflows) aligned to secure SDLC goals. Establish and assess container/Kubernetes security patterns (admission control multi- tenant isolation runtime protection) and supply-chain controls (e.g. SLSA sigstore). Define and assess LLM/agent guardrails (prompt/output handling controls grounding strategies tool allow-listing sandboxing rate limits/quotas and human-in-the-loop patterns) and verify effectiveness through testing. Drive LLM/agent security testing (abuse/misuse cases prompt injection/jailbreak testing tool-use abuse validation adversarial evaluation) and ensure findings are translated into actionable mitigations and risk decisions. Define runtime monitoring and incident response requirements for AI systems (secure telemetry privacy-aware prompt/output logging patterns abuse detection drift signals containment/rollback playbooks). Shape clients enterprise AppSec and AISecOps programsbuild roadmaps aligning security investment with business outcomes and regulatory requirements; define governance metrics and operating model. Serve as the primary day-to-day client interfacebuild rapport and trust with senior stakeholders (e.g. CISOs CTOs Heads of AI/Engineering) and guide prioritization and decision-making. Oversee the quality of project deliverablesassessment reports architectures threat models runbooks and risk/security recommendations. Support business development: define scope build estimates and pricing package proposals and support proposal presentations. Contribute to eminencewhitepapers points-of-view conference contenton the convergence of AppSec DevSecOps and AISecOps. Lead talent processesrecruiting coaching performance management and capability building for AppSec and AI Security professionals. Qualifications Must-have skills / project experience / certifications (AI Security Focus) 6 years of progressively responsible experience in application security DevSecOps product security and/or security architecture with increasing scope and ownership; including 2 years in consulting project leadership or client-facing delivery. Strong knowledge of application API IAM data and cloud security architecture (authn/authz encryption key management secrets network trust boundaries logging/monitoring resiliency and third-party dependencies). Hands-on experience designing or building AI agents/agentic workflows and securing LLM-enabled applications (chatbots/copilots) RAG pipelines and tool/function calling patterns. Hands-on familiarity with agent frameworks and the AI agent stack (e.g. LangGraph LangChain CrewAI AutoGen or equivalent) vector stores evaluation/observability tooling guardrails and sandboxing patternsable to review engineers implementations. Familiarity with MCP (Model Context Protocol) or equivalent agent-to-system integration patterns and ability to guide secure design choices when connecting agents to enterprise systems. Strong understanding of security frameworks/standards such as NIST 800-53 ISO 27001 CIS Controls PCI DSS plus AI-focused guidance such as NIST AI R

Do you love a career where you Experience Grow & Contribute at the same time while earning at least 10% above the market If so we are excited to have bumped onto you.Learn how we are redefining the meaning of work and be a part of the team raved by Clients Job-seekers and Employees.Jobseek...

Do you love a career where you Experience Grow & Contribute at the same time while earning at least 10% above the market If so we are excited to have bumped onto you.
Learn how we are redefining the meaning of work and be a part of the team raved by Clients Job-seekers and Employees.
Jobseeker Video Testimonials
Employee Glassdoor Reviews
If you are a AppSec & AI Security Manager with 8 Yrs looking for excitement challenge and stability in your work then you would be glad to come across this page.
We are an IT Solutions Integrator/Consulting Firm helping our clients hire the right professional for an exciting long-term project. Here are a few details.
Check if you are up for maximizing your earning/growth potential leveraging our Disruptive Talent Solution.
Role: AppSec & AI Security Manager
Location: Hyderabad BanagaloreChennaiPuneGurgaon/New DelhiKolkataMumbai
Experience: 8 to 12 years
Position Summary
We are seeking an AppSec & AI Security Architect to lead and deliver security architecture
reviews and secure-by-design outcomes across modern applications cloud-native platforms
APIs third-party integrations and AI-enabled systems. This role combines deep technical
expertise with delivery leadershipoverseeing teams and engaging senior client stakeholders.
For LLM RAG copilot bot and agentic systems you will evaluate and mitigate risks such as
prompt injection sensitive data disclosure insecure tool/function calling excessive
agency/permissions insecure output handling model and dependency supply-chain risks
training/fine-tuning data leakage and vector database/embedding store weaknesses and
drive adoption of practical guardrails and governance.
As an AppSec & AI Security Manager you will:
Architect and oversee the build of AI agents and agentic workflows for security
automation (e.g. AppSec triage agents security copilots autonomous remediation
workflows AI red-team automation).
Lead end-to-end delivery of AppSec DevSecOps and AI Security (AISecOps)
engagementsmanaging onshore/offshore engineers and architects across the lifecycle
(assess design implement operate).
Define and drive adoption of secure-by-design architectures for modern applications
cloud-native platforms and AI/agentic systems; establish reference architectures and
reusable patterns.
Review and approve security architecture for systems spanning microservices APIs
distributed platforms and AI/RAG/agentic solutions including data flows trust
boundaries secrets encryption and third-party dependencies.
Establish reusable patterns for CI/CD pipeline security policy-as-code IaC scanning
and software/artifact integrity (e.g. SBOM and ML-BOM workflows) aligned to secure
SDLC goals.
Establish and assess container/Kubernetes security patterns (admission control multi-
tenant isolation runtime protection) and supply-chain controls (e.g. SLSA sigstore).
Define and assess LLM/agent guardrails (prompt/output handling controls grounding
strategies tool allow-listing sandboxing rate limits/quotas and human-in-the-loop
patterns) and verify effectiveness through testing.
Drive LLM/agent security testing (abuse/misuse cases prompt injection/jailbreak
testing tool-use abuse validation adversarial evaluation) and ensure findings are
translated into actionable mitigations and risk decisions.
Define runtime monitoring and incident response requirements for AI systems (secure
telemetry privacy-aware prompt/output logging patterns abuse detection drift signals
containment/rollback playbooks).
Shape clients enterprise AppSec and AISecOps programsbuild roadmaps aligning
security investment with business outcomes and regulatory requirements; define
governance metrics and operating model.
Serve as the primary day-to-day client interfacebuild rapport and trust with senior
stakeholders (e.g. CISOs CTOs Heads of AI/Engineering) and guide prioritization and
decision-making.
Oversee the quality of project deliverablesassessment reports architectures threat
models runbooks and risk/security recommendations.
Support business development: define scope build estimates and pricing package
proposals and support proposal presentations.
Contribute to eminencewhitepapers points-of-view conference contenton the
convergence of AppSec DevSecOps and AISecOps.
Lead talent processesrecruiting coaching performance management and capability
building for AppSec and AI Security professionals.

Requirements

Qualifications
Must-have skills / project experience / certifications (AI Security Focus)
6 years of progressively responsible experience in application security DevSecOps
product security and/or security architecture with increasing scope and ownership;
including 2 years in consulting project leadership or client-facing delivery.
Strong knowledge of
Required Skills:
Position Summary We are seeking an AppSec & AI Security Architect to lead and deliver security architecture reviews and secure-by-design outcomes across modern applications cloud-native platforms APIs third-party integrations and AI-enabled systems. This role combines deep technical expertise with delivery leadershipoverseeing teams and engaging senior client stakeholders. For LLM RAG copilot bot and agentic systems you will evaluate and mitigate risks such as prompt injection sensitive data disclosure insecure tool/function calling excessive agency/permissions insecure output handling model and dependency supply-chain risks training/fine-tuning data leakage and vector database/embedding store weaknesses and drive adoption of practical guardrails and governance. As an AppSec & AI Security Manager you will: Architect and oversee the build of AI agents and agentic workflows for security automation (e.g. AppSec triage agents security copilots autonomous remediation workflows AI red-team automation). Lead end-to-end delivery of AppSec DevSecOps and AI Security (AISecOps) engagementsmanaging onshore/offshore engineers and architects across the lifecycle (assess design implement operate). Define and drive adoption of secure-by-design architectures for modern applications cloud-native platforms and AI/agentic systems; establish reference architectures and reusable patterns. Review and approve security architecture for systems spanning microservices APIs distributed platforms and AI/RAG/agentic solutions including data flows trust boundaries secrets encryption and third-party dependencies. Establish reusable patterns for CI/CD pipeline security policy-as-code IaC scanning and software/artifact integrity (e.g. SBOM and ML-BOM workflows) aligned to secure SDLC goals. Establish and assess container/Kubernetes security patterns (admission control multi- tenant isolation runtime protection) and supply-chain controls (e.g. SLSA sigstore). Define and assess LLM/agent guardrails (prompt/output handling controls grounding strategies tool allow-listing sandboxing rate limits/quotas and human-in-the-loop patterns) and verify effectiveness through testing. Drive LLM/agent security testing (abuse/misuse cases prompt injection/jailbreak testing tool-use abuse validation adversarial evaluation) and ensure findings are translated into actionable mitigations and risk decisions. Define runtime monitoring and incident response requirements for AI systems (secure telemetry privacy-aware prompt/output logging patterns abuse detection drift signals containment/rollback playbooks). Shape clients enterprise AppSec and AISecOps programsbuild roadmaps aligning security investment with business outcomes and regulatory requirements; define governance metrics and operating model. Serve as the primary day-to-day client interfacebuild rapport and trust with senior stakeholders (e.g. CISOs CTOs Heads of AI/Engineering) and guide prioritization and decision-making. Oversee the quality of project deliverablesassessment reports architectures threat models runbooks and risk/security recommendations. Support business development: define scope build estimates and pricing package proposals and support proposal presentations. Contribute to eminencewhitepapers points-of-view conference contenton the convergence of AppSec DevSecOps and AISecOps. Lead talent processesrecruiting coaching performance management and capability building for AppSec and AI Security professionals. Qualifications Must-have skills / project experience / certifications (AI Security Focus) 6 years of progressively responsible experience in application security DevSecOps product security and/or security architecture with increasing scope and ownership; including 2 years in consulting project leadership or client-facing delivery. Strong knowledge of application API IAM data and cloud security architecture (authn/authz encryption key management secrets network trust boundaries logging/monitoring resiliency and third-party dependencies). Hands-on experience designing or building AI agents/agentic workflows and securing LLM-enabled applications (chatbots/copilots) RAG pipelines and tool/function calling patterns. Hands-on familiarity with agent frameworks and the AI agent stack (e.g. LangGraph LangChain CrewAI AutoGen or equivalent) vector stores evaluation/observability tooling guardrails and sandboxing patternsable to review engineers implementations. Familiarity with MCP (Model Context Protocol) or equivalent agent-to-system integration patterns and ability to guide secure design choices when connecting agents to enterprise systems. Strong understanding of security frameworks/standards such as NIST 800-53 ISO 27001 CIS Controls PCI DSS plus AI-focused guidance such as NIST AI R