[743SVOSL] AI Security Engineer

ZettaMine Labs Pvt. Ltd.; Hyderabad; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

ZettaMine Labs Pvt. Ltd. is hiring an AI Security Engineer – Senior Level 1 in Hyderabad to lead security-centric AI initiatives across the software development lifecycle.

You will map developer workflows, design AI-powered security solutions, and build AI agents to automate security tasks. The role requires 7–10 years in software/security roles, hands-on GenAI learning, and strong knowledge of secure coding, OWASP, SAST/DAST/IAST, and cloud platforms.

Qualifications

• 7+ years of experience in Software Engineering, Security Engineering, Application Security, Product Security, or related areas.
• 3+ years of hands-on experience developing AI/ML/GenAI solutions in enterprise environments.
• Strong experience in Application Security / Product Security / DevSecOps / Secure SDLC.
• Hands-on experience with LLMs such as Azure OpenAI, OpenAI, Anthropic, or similar platforms.
• Strong understanding of AI Agents, Agentic Workflows, and AI orchestration frameworks.
• Hands-on experience with RAG, embeddings, vector databases, and knowledge retrieval systems.
• Strong knowledge of Secure SDLC, Threat Modeling, OWASP Top 10, SAST, DAST, IAST, SCA, Secrets Management, and Secure Coding.
• Experience with APIs, microservices, and cloud-native architectures.
• Experience with Azure, AWS, or Google Cloud.

Responsibilities

• Analyze and map end-to-end developer workflows across planning, coding, testing, CI/CD, deployment, and operations.
• Design, build, and assess AI-powered solutions to improve developer productivity and engineering efficiency.
• Develop AI agents and copilots to automate repetitive engineering and product security tasks.
• Implement RAG architectures and enterprise knowledge systems using internal documentation, security standards, and best practices.
• Build integrations across GitHub, GitLab, Jira, Azure DevOps, Jenkins, and IDE platforms.
• Identify development workflow bottlenecks and recommend AI-driven process improvements while maintaining security standards.
• Act as an Application Security SME for AI-enabled development initiatives.
• Embed security controls, secure coding guidance, and security best practices directly into developer workflows.
• Define approaches for secure code generation and AI-assisted software development.
• Integrate SAST, DAST, IAST, SCA, secrets detection, IaC scanning, and container security into AI-powered solutions.
• Develop and enforce security guardrails for AI-generated code and AI agents.
• Evaluate and mitigate risks associated with LLMs, AI agents, and autonomous software development.
• Drive Secure SDLC and DevSecOps practices across engineering teams.
• Design, develop, and deploy production-grade applications using C#, ASP.NET, SQL Server, and modern AI frameworks.
• Develop agentic workflows using LLMs and orchestration frameworks.
• Create AI evaluation frameworks to measure model effectiveness, security, quality, and developer adoption.
• Work with large-scale datasets and telemetry to generate actionable engineering and security insights.
• Develop APIs, microservices, services, and enterprise integrations supporting AI capabilities.
• Collaborate with Engineering, Product Security, Platform Engineering, DevOps, and Developer Experience teams.
• Present technical findings, security recommendations, and AI adoption insights to technical leaders and executives.
• Contribute to the organization\'s secure enterprise AI strategy.

Skills

Software Engineering

Security Engineering

Application Security

AI/ML/GenAI

LLMs

AI Agents

RAG

Threat Modeling

Secure Coding

CI/CD

Tools

Azure OpenAI

OpenAI

Anthropic

Checkmarx

Veracode

Fortify

Snyk

Semgrep

SonarQube

GitHub Advanced Security

GitHub

GitLab

Jira

Azure DevOps

Jenkins

Job description

We are looking for AI Security Engineer – Senior Level 1 with exciting project opportunities.

Job Role:

AI Security Engineer – Senior Level 1

Notice Period:

Immediate / 15 Days

Experience:

7–10 Years

Mandatory:

• 7+ years of experience in Software Engineering, Security Engineering, Application Security, Product Security, or related areas
• 3+ years of hands‑on experience developing AI/ML/GenAI solutions in enterprise environments
• Strong experience in Application Security / Product Security / DevSecOps / Secure SDLC
• Hands‑on experience with LLMs such as Azure OpenAI, OpenAI, Anthropic, or similar platforms
• Strong understanding of AI Agents, Agentic Workflows, and AI orchestration frameworks
• Hands‑on experience with RAG, embeddings, vector databases, and knowledge retrieval systems
• Strong knowledge of Secure SDLC, Threat Modeling, OWASP Top 10, SAST, DAST, IAST, SCA, Secrets Management, and Secure Coding
• Experience with APIs, microservices, and cloud‑native architectures
• Experience with Azure, AWS, or Google Cloud

Good‑to‑Have:

• Experience with GitHub, GitLab, Jira, Azure DevOps, Jenkins, and IDE integrations
• Experience developing AI‑powered developer copilots and security automation
• Experience integrating SAST, DAST, SCA, Secrets Detection, IaC Scanning, and Container Security
• Knowledge of Checkmarx, Veracode, Fortify, Snyk, GitHub Advanced Security, Semgrep, SonarQube, or similar tools
• Experience with C#, ASP.NET, and SQL Server
• Experience working with large-scale engineering datasets and telemetry
• Knowledge of AI evaluation frameworks, AI security guardrails, and LLM risk assessment
• Experience with RAG‑based enterprise knowledge systems
• Exposure to CI/CD and modern software delivery practices

Key Responsibilities:

• Analyze and map end‑to‑end developer workflows across planning, coding, testing, CI/CD, deployment, and operations.
• Design, build, and assess AI‑powered solutions to improve developer productivity and engineering efficiency.
• Develop AI agents and copilots to automate repetitive engineering and product security tasks.
• Implement RAG architectures and enterprise knowledge systems using internal documentation, security standards, and best practices.
• Build integrations across GitHub, GitLab, Jira, Azure DevOps, Jenkins, and IDE platforms.
• Identify development workflow bottlenecks and recommend AI‑driven process improvements while maintaining security standards.
• Act as an Application Security SME for AI‑enabled development initiatives.
• Embed security controls, secure coding guidance, and security best practices directly into developer workflows.
• Define approaches for secure code generation and AI‑assisted software development.
• Integrate SAST, DAST, IAST, SCA, secrets detection, IaC scanning, and container security into AI‑powered solutions.
• Develop and enforce security guardrails for AI‑generated code and AI agents.
• Evaluate and mitigate risks associated with LLMs, AI agents, and autonomous software development.
• Drive Secure SDLC and DevSecOps practices across engineering teams.
• Design, develop, and deploy production‑grade applications using C#, ASP.NET, SQL Server, and modern AI frameworks.
• Develop agentic workflows using LLMs and orchestration frameworks.
• Create AI evaluation frameworks to measure model effectiveness, security, quality, and developer adoption.
• Work with large‑scale datasets and telemetry to generate actionable engineering and security insights.
• Develop APIs, microservices, services, and enterprise integrations supporting AI capabilities.
• Collaborate with Engineering, Product Security, Platform Engineering, DevOps, and Developer Experience teams.
• Present technical findings, security recommendations, and AI adoption insights to technical leaders and executives.
• Contribute to the organization's secure enterprise AI strategy.

Who Can Apply?

• 7+ years of experience in Software Engineering, Security Engineering, Application Security, Product Security, or related areas.
• 3+ years of hands‑on experience developing AI/ML/GenAI solutions in enterprise environments.
• Strong hands‑on experience with LLMs, Generative AI, AI Agents, and Agentic Workflows.
• Experience with Azure OpenAI, OpenAI, Anthropic, or similar LLM platforms.
• Strong experience with RAG, embeddings, vector databases, and knowledge retrieval systems.
• Hands‑on experience with AI Agent frameworks and orchestration platforms.
• Strong understanding of Application Security, Product Security, DevSecOps, and Secure SDLC.
• Strong knowledge of OWASP Top 10, Threat Modeling, SAST, DAST, IAST, SCA, Secrets Management, and Secure Coding.
• Experience reviewing code and identifying security vulnerabilities and secure coding issues.
• Hands‑on experience with security tools such as Checkmarx, Veracode, Fortify, Snyk, GitHub Advanced Security, Semgrep, or SonarQube.
• Strong understanding of APIs, Microservices, Cloud‑Native Architecture, and CI/CD.
• Experience with Azure, AWS, or Google Cloud.
• Experience integrating AI solutions with developer and DevOps platforms.
• Strong understanding of AI security risks, LLM security, AI guardrails, and AI‑agent security.
• Excellent communication, collaboration, and stakeholder management skills.