Job Summary

Senior Software Engineer - DevOps for Workflow Innovation @ Barco

Location: Noida, UP, IN

We are seeking a hands-on DevOps Engineer to join the Barco CTRL Workflow Innovation team and support the development of a new AI-driven product from the ground up. The ideal candidate must have strong experience in GCP, cloud-native DevOps, and AI/MLOps practices, with proven ability to build reliable platforms, automation, CI/CD workflows, and deployment infrastructure for data and AI product capabilities.

Responsibilities

- Build and maintain cloud-native DevOps and AI/MLOps infrastructure for the Workflow Innovation product on GCP.
- Design and implement CI/CD workflows for backend services, data pipelines, AI/ML components, model integration, and GenAI-enabled capabilities.
- Automate infrastructure provisioning, environment management, configuration, and deployment workflows using infrastructure-as-code practices.
- Enable deployment and operation of AI/ML workloads, including model serving, inference workflows, RAG-based components, vector search services, and related data/AI services.
- Support cloud-to-edge deployment and operational patterns for AI capabilities, including lightweight model packaging, inference deployment, monitoring, and lifecycle management for Edge AI scenarios.
- Establish observability, monitoring, logging, alerting, reliability, and cost-awareness practices for cloud-native Data & AI product capabilities.
- Support secure handling of product data, secrets, access control, compliance needs, and cloud security best practices.
- Work closely with Data & AI engineers and product teams to improve developer experience, release readiness,



test automation, and operational reliability.
- Guide and mentor fellow colleagues in DevOps, cloud, and AI/MLOps practices while contributing to technical discussions and engineering excellence.

Education

- B. Tech. /B. E. /M. E. /M. Tech. in Computer Science/AI Engineering

Experience

- 6-9 years of hands-on experience in DevOps, cloud platform engineering, SRE, AI/MLOps, or related product engineering roles.
- Strong hands-on experience with GCP is required, including relevant cloud-native compute, storage, networking, IAM, observability, and deployment services.
- Experience designing and implementing CI/CD pipelines for cloud-native applications, backend services, data pipelines, and AI/ML workloads.
- Hands-on experience with AI/MLOps practices, including model deployment, model serving, inference workflows, experiment tracking, model versioning, and release automation for AI-enabled product features.
- Experience with containerization and orchestration technologies such as Docker and Kubernetes.
- Experience with infrastructure-as-code and environment automation using tools such as Terraform, Helm, or equivalent technologies.
- Good understanding of cloud security practices, including IAM, secrets management, network security, secure deployment patterns,



and least-privilege access.
- Experience setting up monitoring, logging, alerting, dashboards, SLO/SLA-oriented reliability practices, and incident response workflows.
- Exposure to data and AI platforms or services such as BigQuery, Vertex AI Vector Search, Dataflow, Dataproc, Cloud Run, GKE, Pub/Sub, vector databases, or equivalent technologies.
- Experience supporting RAG-based applications, GenAI-enabled services, model APIs, or AI inference platforms is highly desirable.
- Exposure to Edge AI concepts, hybrid cloud-edge deployments, on-device or near-device inference, model optimization, and operational constraints such as latency, reliability, connectivity, and resource usage is desirable.
- Good programming and scripting experience using Python, Bash, or similar languages, with ability to build automation and internal tooling.
- Understanding of DevSecOps practices, automated testing, quality gates, vulnerability scanning, dependency management, and secure software supply chain practices.
- Ability to collaborate with cloud partners, architects, Data & AI engineers, developers, product owners, and validation teams across geographies.
- Strong problem-solving mindset, ownership, operational discipline, and willingness to explore and adopt recent technologies in AI, DevOps, and cloud engineering.

Disclaimer: This job description has been sourced from a public domain and may have been modified by Naukri.com to improve clarity for our users. We encourage job seekers to verify all details directly with the employer via their official channels before applying.

📌 Senior Software Engineer - DevOps (Noida)
🏢 Barco
📍 Noida