Sr. AI Developer Engineer – DevSecOps Tools (L3)

Job Title: Sr. AI Developer Engineer – DevSecOps Tools (L3)

Location: Reliance Corporate Park (RCP), Navi Mumbai

Working Hours: 9:00 AM – 6:00 PM

Mode of Interview: Face-to-Face or MS Teams

Position Summary

As part of the DevSecOps Tools vertical, the Sr. AI Developer Engineer – DevSecOps Tools is a hands-on developer role focused on building AI-powered automation that embeds security natively into CI/CD pipelines and the software delivery lifecycle. Working under the direction of the Lead Engineer, this role will develop intelligent security scan orchestration, ML-driven pipeline anomaly detection, and LLM-based remediation tools for IaC and container security. The engineer writes production-quality code, maintains deployed automations, and continuously improves pipeline security coverage in a pure individual contributor role with no people-management responsibilities.

Requirements

Key Responsibilities

• CI/CD Security Automation: Build AI-powered security automation that integrates natively into CI/CD pipelines (Azure DevOps, GitHub Actions, Jenkins, GitLab CI) to enforce policy-as-code, security gates, and pre-merge vulnerability checks.
• Pipeline Anomaly Detection: Develop ML models to detect pipeline anomalies, flagging unusual code commits, suspicious dependency changes, and build-time integrity violations before deployment to production.
• IaC Remediation Assistants: Build LLM-powered Infrastructure as Code (IaC) remediation assistants that detect misconfigurations in Terraform, ARM templates, and Helm charts (via Checkov, Terrascan) and auto-generate corrected code snippets.
• Contextual In-Pipeline RAG: Implement RAG pipelines over internal security policies, hardening baselines, and compliance frameworks to deliver contextual, in-pipeline remediation guidance directly to software developers.
• Agentic Multi-Tool Orchestration: Develop agentic AI workflows that orchestrate multi-tool security scans (SAST, SCA, container scanning, secrets detection), aggregate scan results, and auto-raise prioritized tickets for critical findings.

• Scan Report NLP Pipelines: Build and fine-tune NLP models to parse, categorize, and summarize findings across heterogeneous security scan report formats.

• Experience: 4–6 years of relevant experience in AI/ML development, DevSecOps engineering, or security automation.
• Education: B.Tech or M.Tech in Computer Science, Information Technology, AI/ML, or a related technical field.
• Certifications: CompTIA Security+, CEH, CKS (Certified Kubernetes Security Specialist), or SC-200.
• Technical Stack: Python, CI/CD tools (GitHub Actions, Jenkins, Azure DevOps, GitLab CI), IaC tools (Terraform, Checkov), LLMs, RAG, NLP libraries, and container security scanners.