Senior Software Engineer - DevOps

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 new technologies in AI, DevOps, and cloud engineering.

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