Website:
netrolynx.ai
Job details:
About Infinite Electronics
Infinite Electronics is a global manufacturer specializing in high-performance connectivity solutions. Serving a diverse range of industries, the company emphasizes precision-engineered components and assemblies designed to meet complex technical requirements. With a strong focus on innovation and engineering excellence, Infinite Electronics collaborates closely with its customers to address real-world challenges, accelerate product development, and deliver reliable, scalable solutions that drive technological advancement.
About Infinite India (GCC)
Infinite Electronics is establishing its India Global Capability Center (GCC) in Pune to expand its engineering, digital, and customer service capabilities. This center aims to support mission-critical initiatives while working in close collaboration with global stakeholders. Located at Mont Clare, Baner, the center offers a modern workspace designed to foster collaboration, innovation, and long-term career growth. As an early team member, you will have the opportunity to influence the center's operations, set technology standards, and develop scalable processes from the ground up. This role provides a unique platform to grow professionally within an organization committed to long-term excellence and capability building.
Why Join
Joining Infinite Electronics' India GCC offers a unique opportunity to build foundational systems and standards from the outset. You will collaborate directly with international teams, gaining valuable global exposure that enhances your professional development. The modern work environment in Pune is designed to support innovation and career growth, with a focus on long-term capability expansion. The company emphasizes a culture of ownership, continuous improvement, and excellence, making it an ideal environment for driven professionals seeking to make a significant impact in the technology space.
Position Name: Azure DevOps Engineer
Location: Pune, India
Exempt / Non-Exempt: Exempt
Reports To: Sr. Manager of Software Development Engineering, US
About The Role
The Azure DevOps Engineer at Infinite Electronics is a hands-on cloud platform and infrastructure specialist based in Pune. Reporting directly to the U.S. engineering leadership, this role involves working within a dedicated AI engineering team to design, operate, and secure cloud infrastructure, CI/CD pipelines, and MLOps platforms that support enterprise applications, data pipelines, and AI/GenAI workloads in production. The role is delivery-focused, requiring ownership of platform operations end-to-end—from environment provisioning and deployment automation to monitoring, incident response, and continuous improvement. The engineer will be responsible for deploying, managing, and maintaining AI models and agents on the production AI platform, ensuring high reliability, security, and compliance while supporting rapid delivery cycles.
The ideal candidate will be equally comfortable writing infrastructure-as-code, troubleshooting infrastructure failures, building CI/CD pipelines for application and AI/ML artifacts, and implementing observability for distributed systems. Collaboration with U.S. teams will be a daily activity, requiring effective communication and coordination across time zones. This role also involves supporting critical releases, deployments, and incident management, occasionally outside of standard working hours.
Qualifications
Required Experience:
- Bachelor’s degree in computer science, Engineering, or a related technical field, or equivalent practical experience.
- Extensive experience designing, building, and operating production-grade cloud infrastructure and platform services, with ownership of reliability, security, and operational outcomes. Preference for Azure experience; AWS or GCP experience is also valued.
- Deep understanding of cloud compute, networking, identity and access management, and storage services, with a focus on secure, scalable, multi-environment architectures across Dev, Stage, and Production.
- Proficiency in CI/CD pipeline design and automation supporting application code, infrastructure-as-code, data pipelines, and AI/ML artifacts, with familiarity with deployment strategies like blue/green and canary releases.
- Hands-on experience with infrastructure-as-code tools such as Bicep or Terraform for environment provisioning and configuration management.
- Proven ability to implement monitoring, logging, tracing, and alerting for distributed systems, with a focus on SLA/SLO adherence, incident management, root cause analysis, and system stabilization.
- Strong knowledge of cloud security practices, including RBAC, secrets management, network isolation, and compliance requirements.
- Ability to deliver incremental platform improvements, communicate tradeoffs clearly, and prioritize platform reliability and security as core responsibilities.
- Comfort with using AI coding assistants within development workflows, with the judgment to validate and own AI-generated code and configurations in production.
Preferred Experience
- Master’s degree in computer science, Engineering, or related fields.
- Experience supporting deployment, operation, and lifecycle management of AI models and agents, including versioning, deployment pipelines, monitoring, drift detection, and lifecycle management on platforms such as Azure AI Foundry, Azure Machine Learning, or equivalent services on AWS or GCP.
- Experience implementing observability for AI systems, including metrics like inference latency, throughput, error rates, and drift indicators.
- Proficiency with containerization and orchestration tools such as Docker, Kubernetes, AKS, EKS, or GKE.
- Knowledge of cost optimization strategies and performance tuning for cloud workloads.
- Expertise in end-to-end CI/CD pipelines for code, data, and models to ensure reproducibility and environment consistency.
- Understanding of responsible AI, governance, and compliance frameworks relevant to enterprise AI deployments.
- Hands-on experience within the Microsoft Azure ecosystem, including services like App Service,
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