CI/CD Engineer

Role Overview

We are seeking a highly skilled CI/CD Engineer to design, implement, and support end-to-end automation pipelines across application development, data/ML workflows, and AI/LLM deployments. The role includes ownership of integration and deployment services, embedding security-first (DevSecOps) practices, and extending governance to MLOps and LLM SecOps ecosystems.

Key Responsibilities

• Design, develop, and maintain scalable backend and full-stack applications
• Build RESTful APIs and microservices using Node.js, TypeScript, Python, and Java
• Write clean, efficient, and maintainable code following best practices
• Collaborate with cross-functional teams (DevOps, QA, Product) to deliver high-quality solutions
• Participate in system design discussions and contribute to architecture decisions
• Optimize application performance, scalability, and reliability
• Conduct code reviews and ensure adherence to coding standards
• Debug, troubleshoot, and resolve production issues
• Work with databases (SQL/NoSQL) for data modeling and integration
• Contribute to CI/CD pipelines and automated testing frameworks
  
  

Qualifications & Experience

CI/CD Pipeline Engineering

Design, build, and maintain scalable CI/CD pipelines for application, data, ML, and AI systems.

Automate build, test, integration, and deployment workflows across cloud (Azure/AWS/GCP) and on-prem platforms.

Implement multi-stage pipelines (build → test → security scan → deploy → monitor).

Integrate source control systems (GitHub, GitLab, Azure DevOps).

Integration & Deployment Services

Support enterprise integration services (APIs, microservices, event-driven architectures).

Develop and maintain deployment strategies:

• Blue/Green deployments
• Canary releases
• Feature toggles

Manage containerized deployments (Docker, Kubernetes).

Ensure environment consistency using IaC tools (Terraform, Bicep, ARM).

DevSecOps Implementation

Embed security controls in CI/CD pipelines:

• SAST, DAST, SCA, Container scanning
• Secrets scanning and credential management

Implement policy-as-code and compliance automation.

Integrate tools like:

• SonarQube, Checkmarx
• Aqua, Prisma Cloud, Trivy

Ensure compliance with security standards (ISO, SOC2, GDPR).

MLOps / ML SecOps

Build and maintain ML pipelines for:

Model training, validation, deployment, monitoring

Enable ML lifecycle automation (data → model → deployment → retraining).

Integrate tools such as:

MLflow, Kubeflow, Azure ML, SageMaker

Apply ML security practices:

Data integrity checks

Model drift detection

Adversarial robustness validation

Ensure reproducibility and traceability of ML experiments.

LLM SecOps (AI Governance & Security)

Implement secure deployment pipelines for LLM-based applications.

Monitor and enforce controls for:

• Prompt injection risks
• Data leakage & sensitive information exposure
• Model misuse / hallucination tracking

Enable AI model governance:

Versioning, audit trails, explainability

Integrate LLM observability tools (prompt monitoring, response evaluation).

Apply Responsible AI practices (bias detection, fairness, compliance).

Monitoring & Reliability Engineering

Implement observability frameworks using:

Prometheus, Grafana

Azure Monitor, ELK Stack

Track:

Pipeline health

Deployment success rates

Security posture

Ensure high availability and resilience of CI/CD systems.

Collaboration & Stakeholder Management

Work closely with:

• Development teams
• Data scientists / ML engineers
• Security teams
• Drive adoption of DevOps culture and best practices.
• Provide support for release management and incident resolution.
  
  

Educational Background

• B.Tech/B.S./ M.S. in Computer Science, Statistics, Mathematics, or a related field
  
  

Additional Skills & Preferred Qualifications

• Strong communication, stakeholder management, and organizational skills
• Self-motivated, customer-focused, and detail-oriented mindset
• Certification in:
• Azure DevOps / AWS DevOps
• Kubernetes (CKA/CKAD)
• Experience with AI governance frameworks
• Background in data engineering or ML engineering
• Experience working in Agile/Scrum environments
• Knowledge of ERP systems (SAP) – strongly preferred
• Six Sigma Yellow Belt or Green Belt certification – a plus
• ITIL certification – a plus
  
  

Any Questions

Mukund.Dighe&mahle.com