Job Summary

Senior Software Engineer- DevOps for Workflow Innovation in Barco Control Rooms @ Barco

Location: Noida

As a Senior Software Engineer - DevOps in the Workflow Innovation team, you will be responsible for building and maintaining the cloud-native engineering foundation required to develop, test, deploy, and operate AI-driven product capabilities for Barco Control Rooms. This is not a classical DevOps role focused only on build pipelines and deployments; it requires hands-on experience with AI/MLOps, cloud infrastructure, data/AI workloads, automation, observability, and secure production operations. The role will also support deployment patterns where AI capabilities may need to run closer to the operational environment, including Edge AI scenarios, hybrid cloud-edge architectures, and effective inference workflows for mission-critical control room use cases. You will collaborate with cloud partners, product owners, architects, Data AI engineers, developers, and validation teams across locations to enable fast, reliable, and secure delivery of workflow innovation 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.

Qualifications and Experience

We are seeking experience with the following technologies/domains:

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.

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Senior Software Engineer (Noida)
🏢 Barco
📍 Noida