Senior Solutions Architect

S
Sibros TechnologiesAutomotive Software
India, Flexible working hours to accommodate different time zones.Full-TimeSenior
Salary not disclosed
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Job Details

Experience
15+ years of experience across specific technology domain areas; 5+ years of hands-on experience designing, implementing, or consulting on complex cloud applications and infrastructure architectures.
Required Skills
AWSGCPIoTKubernetesApache KafkaDevOps

Requirements

  • 15+ years of experience across software development, cloud computing, systems engineering, infrastructure, networking, security, and data analytics.
  • 5+ years of hands-on experience designing, implementing, or consulting on complex cloud applications and infrastructure architectures.
  • Working knowledge of real-time and batch data processing at scale using MQTT, Apache Kafka, and Kubernetes.
  • Experience with time-series databases and data analytics tools applied to connected vehicles.
  • Working knowledge of major hyperscalers such as AWS and GCP.
  • Proficiency with IoT/edge computing, data lakes, AI/ML, HPC, and DevOps/CI-CD pipelines.
  • Proven ability to communicate complex technical concepts to technical teams and executive stakeholders.
  • Experience integrating cloud-native SDV architectures with legacy OEM software and enterprise backends like PLM, MES, and SAP.
  • Background in leading developer teams utilizing AI-assisted development tooling.
  • Familiarity with multi-region technical requirements and delivery models across India, EU, and Japan.

Responsibilities

  • Serve as the primary technical point of contact and trusted advisor for Automotive OEM accounts across India, EU, and Japan.
  • Architect and design scalable, secure, and cost-effective cloud solutions for connected vehicle systems and SDV data platforms.
  • Lead proof-of-concept (PoC) engagements, conduct architectural reviews, and actively support customer RFP processes.
  • Lead and manage a team of developers to design and deliver custom, customer-focused solutions using AI-assisted development tools.
  • Direct integrations with enterprise software ecosystems, including MES, PLM, After Sales Systems, SAP, and custom cloud workflows.
  • Collaborate with internal Product, Engineering, Infrastructure, and Customer Success teams to translate business objectives into technical solutions.
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