Senior Developer Operations Engineer

About the role

We are looking for an outstanding Senior DevOps Engineer to join Aura, our revolutionary, large-scale mobile content discovery platform used by millions of users worldwide. In this role, you won't just keep the lights on-you will take a leading role in shaping our data infrastructure, setting architectural standards for AI/ML workloads, and bridging the gap between DevOps and Data Engineering. Why you'll love this team: We move fast, use cutting-edge technologies, and value absolute technical excellence over rigid bureaucracy. If you are passionate about solving complex, high-traffic infrastructure puzzles and want to see your work directly impact millions of daily users, this is the sandbox you've been looking for.

Responsibilities

• Design Data-Native Cloud Solutions: Design and implement scalable data and AI/ML infrastructure across multiple environments using Kubernetes, orchestration platforms, and IaC to power our AI, ML, and analytics ecosystem
• Accelerate Data/ML Engineer Experience: Spearhead improvements to data pipeline deployment, monitoring tools, and self-service capabilities that empower data teams to deliver insights faster with higher reliability
• Engineer Robust Data/ML Platforms: Build and optimize infrastructure that supports diverse data workloads from real-time streaming to batch processing, ensuring performance and cost-effectiveness for critical analytics systems
• Drive DevOps Excellence: Collaborate with engineering leaders across backend and ML teams, champion modern infrastructure practices, and mentor team members to elevate how we build, deploy, and operate data systems at scale
• Collaborate on high-level technical designs with ML and Backend engineers to build resilient systems

Requirements

• 5+ years of hands-on DevOps experience building, shipping, and operating production systems
• Infrastructure as Code: design and implement infrastructure automation using tools such as Terraform, Pulumi, or CloudFormation (modular code, reusable patterns, pipeline integration)
• Cloud platforms: deep experience with AWS, GCP, or Azure (core services, networking, IAM)
• Kubernetes: strong end-to-end understanding of Kubernetes as a system (routing/networking, scaling, security, observability, upgrades), with proven experience integrating data-centric components (e.g., Kafka, RDS, BigQuery, Aerospike).
• GitOps & CI/CD: practical experience implementing pipelines and advanced delivery using tools such as Argo CD / Argo Rollouts, GitHub Actions, or similar
• Observability: metrics, logs, and traces; actionable alerting and SLOs using tools such as Prometheus, Grafana, ELK/EFK, OpenTelemetry, or similar
• Scalability & Performance: Proven experience managing production environments characterized by high traffic volumes and large amounts of data, with a focus on maintaining system reliability and cost-efficiency at scale.
• You might also have
• Coding proficiency in at least one language (e.g., Python or TypeScript); able to build production-grade automation and tools.
• Data Pipeline Orchestration: Demonstrated success building and optimizing data pipeline deployment using modern tools (Airflow, Temporal, Kubernetes operators) and implementing GitOps practices for data workloads
• Data Engineer Experience Focus: Track record of creating and improving self-service platforms, deployment tools, and monitoring solutions that measurably enhance data engineering team productivity
• Data Infrastructure Deep Knowledge: Extensive experience designing infrastructure for data-intensive workloads including streaming platforms (Kafka, Kinesis), data processing frameworks (Spark, Flink), storage solutions, and comprehensive observability systems
• Additional information
• Relocation support is not available for this position
• Work visa/immigration sponsorship is not available for this position

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