Principal Engineer

Elektrobit Automotive · Bangalore

Source and collection record

Last observed by our collector: 8 October 2026 at 11:22 pm IST. This is not a manual review or a confirmation from the employer.

Employer requisition: 1184

Job type and experience labels are automated discovery categories. The employer determines eligibility. Original experience wording was not retained separately; check the current employer page.

How sourcing and classification work · Report a discrepancy

Your application evidence checklist

Mark the statements you can support after reading the employer source. This checklist stays on this page; it does not score your eligibility or submit an application.

Collected minimum qualification: 15+ years of experience in Software Engineering, Cloud, DevOps, or Platform Engineering.Attendance and availability: I checked the employer page for work location, office attendance, start date and duration.Current requisition: I checked the current employer requisition and its application requirements.

0 of 3 checks marked. Keep unresolved requirements as questions for the employer.

Collected role description

Overview We are seeking a Principal Engineer – AI Platforms, MLOps & AIOps with 15+ years of experience in Software Engineering, Cloud, DevOps, and AI Platform Engineering. This role will define the technical strategy, architecture, and governance of enterprise AI platforms while driving scalable AI adoption and operational excellence across the organization. Responsibilities Technical Leadership & Architecture Define the roadmap and architecture for enterprise AI platforms, MLOps, and AIOps. Establish standards for AI model development, deployment, monitoring, and governance. Drive technology evaluation and adoption of emerging AI platform capabilities. Ensure scalability, reliability, security, and cost optimization of AI infrastructure. MLOps & AIOps Enablement Lead the implementation of enterprise MLOps frameworks and automation pipelines. Enable efficient model training, deployment, monitoring, and lifecycle management. Drive AIOps initiatives including intelligent monitoring, anomaly detection, and operational automation. Promote self-service AI capabilities for engineering and data science teams. Governance & Collaboration Define AI governance, security, compliance, and operational best practices. Collaborate with architects, AI engineers, data scientists, and business stakeholders. Mentor senior engineers and provide technical guidance across teams. Qualifications Experience 15+ years of experience in Software Engineering, Cloud, DevOps, or Platform Engineering. 5+ years leading MLOps, AIOps, or AI platform initiatives. Proven experience architecting and operating large-scale cloud-native platforms. Technical Skills MLOps platforms: MLflow, Kubeflow, Azure ML, SageMaker, Vertex AI, or similar. Cloud platforms: Azure, AWS, or GCP. Docker, Kubernetes, CI/CD, Infrastructure as Code (Terraform, Ansible). Monitoring and observability tools such as Grafana, Prometheus, ELK, Datadog, or Splunk. Python and automation development. Strong understanding of AI governance, security, and model lifecycle management. Success Measures Successful enterprise adoption of AI platforms and MLOps capabilities. Improved deployment speed, platform reliability, and operational efficiency. Scalable, secure, and governed AI infrastructure. Delivery of strategic AI initiatives aligned with business objectives. Sravani, Konanki extern.Konanki.Sravani@elektrobit.com

Collected minimum qualification

15+ years of experience in Software Engineering, Cloud, DevOps, or Platform Engineering.

Collected experience requirement

15+ years of experience