Software Engineer, Infrastructure

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Software Engineer, Infrastructure based in India.

This role offers an exciting opportunity to build and scale the foundational infrastructure powering next-generation AI and large-scale data platforms. As part of a highly technical engineering team, you will design reliable, high-performance systems that support massive datasets, automated deployments, and mission-critical AI workloads. The position combines deep infrastructure engineering with cloud-native technologies, distributed systems, and platform reliability initiatives. You will have significant ownership over architecture decisions, collaborate closely with cross-functional engineering teams, and directly influence the scalability and resilience of enterprise-grade solutions. This is an ideal opportunity for engineers who enjoy solving complex systems challenges, driving automation, and working in a fast-paced, innovation-driven environment.

• Design, implement, and operate cloud infrastructure supporting large-scale distributed systems and data-intensive workloads.
• Build and manage highly available Kubernetes environments with a focus on scalability, resilience, and operational efficiency.
• Develop and optimize CI/CD pipelines to improve deployment reliability, testing automation, and release velocity.
• Enhance developer productivity by automating workflows, reducing operational friction, and improving platform tooling.
• Contribute to end-to-end testing frameworks and release confidence initiatives to ensure system stability.
• Strengthen observability capabilities through the implementation of logging, monitoring, tracing, and alerting solutions.
• Collaborate with engineering teams on infrastructure architecture, reliability engineering, and system scaling strategies.
• Support customer-facing technical integrations, troubleshoot infrastructure-related issues, and ensure reliable deployments across diverse cloud environments.
• Drive operational excellence by implementing infrastructure best practices, automation strategies, and reliability-focused processes.
• Participate in the continuous improvement of platform performance, cost optimization, and engineering efficiency.

Requirements

• Minimum of 5 years of experience in infrastructure engineering, platform engineering, site reliability engineering, or distributed systems development.
• Strong programming skills in languages such as Go, Python, Java, or similar technologies.
• Extensive hands-on experience with Kubernetes in production environments, including cluster management and container orchestration.
• Strong knowledge of cloud platforms, including AWS, Google Cloud Platform (GCP), and/or Microsoft Azure.
• Experience with container technologies such as Docker and cloud-native application architectures.
• Proven expertise in designing and managing CI/CD pipelines and modern deployment practices.
• Strong proficiency with Infrastructure as Code (IaC) tools, particularly Terraform.
• Ability to troubleshoot and resolve complex cross-layer issues involving networking, storage, runtime environments, and distributed systems.
• Demonstrated track record of building scalable, reliable, and cost-efficient infrastructure solutions.
• Strong communication skills and the ability to work effectively in fast-paced, highly collaborative environments.
• Experience with data platforms, lakehouse architectures, or technologies such as Spark, Trino, Iceberg, Delta Lake, or Airflow is considered an advantage.
• Familiarity with observability and monitoring tools such as Prometheus, Grafana, ELK Stack, Datadog, or similar platforms is a plus.
• Strong sense of ownership, problem-solving capabilities, and a passion for infrastructure innovation and continuous improvement.

Benefits

• Competitive compensation package, including performance-based incentives and long-term growth opportunities.
• Meaningful equity participation, allowing employees to contribute to and benefit from organizational success.
• Comprehensive healthcare coverage and employee wellbeing support.
• Flexible paid time off policy promoting work-life balance and personal wellbeing.
• Opportunity to work on cutting-edge AI infrastructure and exabyte-scale data systems.
• Support for continuous learning, research initiatives, conference participation, and professional development activities.
• Collaborative, high-impact engineering culture with significant ownership and technical autonomy.
• Exposure to advanced technologies and complex large-scale engineering challenges within a rapidly growing environment.