Sr. AI Developer Engineer – DevSecOps Tools (L3)

TOCUMULUS; Mumbai; On-site; INR 3,000,000 - 4,200,000; Full time

Job summary

TOCUMULUS is seeking a Sr. AI Developer Engineer – DevSecOps Tools, a hands-on developer role in Navi Mumbai. You will build AI-powered automation to embed security into CI/CD pipelines and the software delivery lifecycle, including ML-driven anomaly detection and remediation tools for IaC and containers.

You will write production-grade code and maintain automations as an individual contributor. The role emphasizes building agentic workflows, integrating SAST/SCA tooling, and delivering

Qualifications

• 4–6 years of relevant experience in AI/ML development, DevSecOps engineering, or security automation.

Responsibilities

• CI/CD Security Automation: Build AI-powered security automation that integrates into CI/CD pipelines.
• Pipeline Anomaly Detection: Develop ML models to detect pipeline anomalies and integrity violations.
• IaC Remediation Assistants: Build LLM-powered IaC remediation assistants for Terraform, ARM templates, and Helm charts.
• Contextual In‑Pipeline RAG: Implement RAG pipelines delivering contextual remediation guidance.
• Agentic Multi-Tool Orchestration: Create workflows to orchestrate multi-tool security scans and raise prioritized tickets.
• Scan Report NLP Pipelines: Develop NLP models to parse and summarize security scan findings.

Skills

AI/ML development

DevSecOps engineering

Security automation

NLP knowledge

Education

B.Tech or M.Tech in CS/IT/AI/ML or related

Tools

GitHub Actions

Jenkins

Azure DevOps

GitLab CI

Terraform

Checkov

LLMs

RAG

NLP libraries

Container security scanners

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

Location: Reliance Corporate Park (RCP), Navi Mumbai

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.

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

Experience: 4–6 years of relevant experience in AI/ML development, DevSecOps engineering, or security automation.

Education

Education: B.Tech or M.Tech in Computer Science, Information Technology, AI/ML, or a related technical field.

Certifications

Certifications: CompTIA Security+, CEH, CKS (Certified Kubernetes Security Specialist), or SC-200.

Technical Stack

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.