AI Security Engineer

Job Description :

Key Responsibilities :

AI-Powered Developer Workflow :

- Analyze and map end-to-end developer workflows across planning, coding, testing, CI/CD, deployment, and operations.

- Design, build and assess AI-powered solutions that improve developer productivity and engineering efficiency.

- Develop AI agents and copilots for product security team to automate repetitive engineering and security tasks.

- Implement Retrieval-Augmented Generation (RAG) and knowledge systems that leverage internal documentation, security standards, and best practices.

- Build integrations across developer tools including GitHub, GitLab, Jira, Azure DevOps, Jenkins, and IDE platforms.

- Identify bottlenecks in development workflows and recommend AI-based process improvements complying with security standards.

Application Security :

- Serve as the Application Security Subject Matter Expert (SME) for AI-enabled development initiatives.

- Embed security controls and guidance directly into developer workflows.

- Define approaches for secure code generation and AI-assisted software development.

- Partner within Product Security teams to integrate SAST, DAST, SCA, secrets detection, IaC scanning, and container security into AI solutions.

- Develop 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 best practices across engineering organizations.

AI Solution Development :

- Design, develop, and deploy production-grade application using C#, Asp.net, SQL server, AI applications using modern AI frameworks.

- Partner with business units to build and assess agentic workflows leveraging LLMs and orchestration frameworks.

- Create evaluation frameworks to measure AI model effectiveness, security, and developer adoption.

- Work with large-scale datasets and telemetry to generate actionable engineering insights.

- Develop APIs, services, and integrations supporting enterprise AI capabilities.

Cross-Functional Collaboration :

- Collaborate with Engineering, Product Security, Platform Engineering, DevOps, and Developer Experience teams.

- Present findings and recommendations to technical leaders and executives.

- Influence enterprise AI strategy for secure software development.

Required Qualifications :

Experience :

- 7+ years of software engineering, security engineering, or related experience.

- 3+ years developing AI, ML, or GenAI solutions in enterprise environments.

- Hands-on experience with developer platforms and modern software delivery practices.

- Prior experience in Application Security, Product Security, DevSecOps, or Secure SDLC programs.

Technical Skills :

- Strong programming skills in Python, Java, JavaScript/TypeScript, or Go.

- Experience with LLM platforms such as Azure OpenAI, OpenAI, Anthropic, or similar.

- Expertise in AI agent frameworks and orchestration platforms.

- Experience with vector databases, embeddings, RAG architectures, and knowledge retrieval systems.

- Strong understanding of APIs, microservices, and cloud-native architectures.

- Experience with Azure, AWS, or Google Cloud.

Application Security Expertise :

- Deep understanding of Secure SDLC, Threat Modeling, OWASP Top 10, SAST, DAST, IAST, Software Composition Analysis (SCA), Secrets Management, Secure Coding Practices.

- Ability to review code and identify security vulnerabilities.

- Familiarity with security tools such as Checkmarx, Veracode, Fortify, Snyk, GitHub Advanced Security, Semgrep, SonarQube, or similar.