Sr. AI Developer Engineer – DevSecOps Tools (L3)

Theomnihire; Mumbai; On-site; INR 300,000 - 600,000; Full time

Job summary

Theomnihire in Mumbai invites applications for a Sr. AI Developer Engineer - DevSecOps Tools. This hands-on role focuses on building AI-powered automation that embeds security into CI/CD and the software delivery lifecycle as an individual contributor.

You will develop ML-driven pipeline anomaly detection, IaC remediation assistants for Terraform/ARM/Helm, and NLP-based scan report summarization, using a modern toolchain (GitHub Actions, Jenkins, Azure DevOps, Checkov).

Qualifications

• 4–6 years of experience in AI/ML development, DevSecOps, or security automation.
• B.Tech or M.Tech in CS/IT/AI/ML or a related field.
• Certifications such as CompTIA Security+, CEH, CKS or SC-200 are preferred.

Responsibilities

• Build AI-powered security automation integrated into CI/CD pipelines (Azure DevOps, GitHub Actions, Jenkins, GitLab CI).
• Develop ML models to detect pipeline anomalies and prevent production issues.
• IaC remediation assistants for Terraform, ARM templates, and Helm charts with auto-generated fixes.
• Implement in-pipeline RAG to provide remediation guidance to developers.
• Orchestrate multi-tool security scans and triage findings into actionable tickets.
• Develop NLP pipelines to parse and summarize security reports.

Skills

Python

CI/CD Tools

Terraform

Checkov

LLMs

NLP

Education

B.Tech/B.E in CS/IT/AI/ML

M.Tech in CS/AI/ML

Certifications: Security+ / CEH / CKS / SC-200

Tools

GitHub Actions

Jenkins

Azure DevOps

Terraform

Checkov

Kubernetes

Docker

Job description

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

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.