CI/CD Engineer

Services

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Together, we move the world—we’ve been doing it for over 100 years. At MAHLE, as a leading international development partner and systems supplier to the automotive industry, we pursue the objective of making mobility more efficient, more environmentally friendly, more convenient, and more economical. As part of our dual strategy, we are working both on the intelligent combustion engine for the use of hydrogen and other nonfossil fuels and on technologies for fuel cells and e\-mobility.

MAHLE generated sales of €11\.3 billion in 2025\. Employing just under 65,000 people at 127 production locations and 11 technology centers, the company is represented in 28 countries. (as at: 12/31/2025\). Join our MAHLE team! \#weshapefuturemobility

• *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:**

1\. 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).

2\. 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).

3\. 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).

4\. 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.

5\. 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).

6\. 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.

7\. 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

IN

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• *Facts about the jobEntry level:** Experienced hires

• *Part\- / Full\-time:** Full Time

• *Functional area:** IT

• *Department:** Services

• *Location:**

Pune, IN

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• *Company:** MAHLE Holding (IN)

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Closing date for applications

Don't waste any time, apply while the position is online.

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Your future at MAHLE

As a team player and someone who thinks ahead, you can deploy all your skills with us. In cooperation with colleagues from different countries and areas, you contribute in designing the mobility of the future. When selecting MAHLE, you choose trend\-setting technologies and strategies. Are you interested in working with us and developing efficient and environmentally\-friendly solutions, optimising existing products, and turning innovative ideas into reality? Then MAHLE is the right address for you.

Shape the future with us.

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