Senior AI Engineer

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.