Infrastructure Automation Engineer

Apple

23h

About The Position

Apple Ads extends the customer experience philosophy to advertising, helping people discover what they need while empowering advertisers to grow their businesses. Our technology delivers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS (Major League Soccer) Season Pass. Every solution we build is rooted in trust, connection, and impact: respecting user privacy, integrating advertising seamlessly into the Apple experience, and delivering value for advertisers of every size—from small app developers to global brands. When advertising is done right, it benefits everyone. Apple Ads, India is seeking Software Engineers to join the Platform Engineering Team in Hyderabad, focused on enhancing the reliability and performance of the Apple Ads platform. In this role, you will design and develop automation that will enable development teams to provision infrastructure as they need and to deploy code across environments. Do you love building highly scalable platforms that enable engineering teams to move faster? Join our Platform Engineering team to design, build, and operate cloud-native platforms that simplify infrastructure, improve developer productivity, and enable reliable delivery of large-scale applications. As a Platform Development Engineer, you will build self-service platform capabilities across cloud infrastructure, Kubernetes, CI/CD, observability, SRE, and developer experience to build secure, scalable, highly available, and automated platforms. You will also explore and leverage AI to automate engineering workflows, improve developer experience, and enhance platform operations.

Requirements

Bachelor's degree in Computer Science, Engineering, or a related technical field with 5+ years of Cloud & Platform engineering.
Strong programming experience in Python & Go or similar languages.
Hands-on experience with AWS (Mandatory), Azure, or GCP and Infrastructure-as-Code such as Terraform, CRD, Helm, ArgoCD, ACK, Kro etc.
Experience building and operating Kubernetes/container platforms in production.
Experience to build & operate data services on AWS (MSK, Glue, EMR, Spark on EKS, Flink on EKS).
Strong experience with CI/CD, Git, GitOps, and deployment automation.
Experience with SRE practices, including SLOs, error budgets, reliability automation, capacity planning, and production engineering.
Experience with observability platforms such as Datadog, Prometheus, Grafana, OpenTelemetry, ELK, or CloudWatch.
Strong software engineering fundamentals and experience building automation, APIs, or reusable engineering frameworks.
Strong problem-solving and communication skills with the ability to work across engineering organisations.

Nice To Haves

Experience building Internal Developer Platforms (IDPs), self-service infrastructure, Golden Paths, developer portals, or platform APIs.
Exposure to data platforms and distributed data frameworks such as Hadoop, Spark, Flink, Kafka, or similar technologies.
Exposure to cloud data services and query engines such as AWS Glue, Athena, EMR, Trino or equivalent technologies.
Experience with workflow/orchestration technologies such as Airflow, Temporal etc.
Experience with multiple public clouds or hybrid cloud environments.
Experience contributing to open-source projects or building reusable engineering frameworks.

Responsibilities

Design, develop, and operate scalable cloud-native platform services on Public Cloud.
Design and operate Kubernetes/container platforms at scale.
Implement secure-by-default platforms covering IAM, VPC, Security Groups, secrets management, encryption, policy enforcement, and DevSecOps.
Implement SRE practices, including SLIs/SLOs, error budgets, capacity planning, incident management, automation, and reliability engineering.
Design, develop, and operate scalable, cloud-native infrastructure for data services on AWS (MSK, Glue, EMR, EKS, Spark on EKS, Flink on EKS).
Develop self-service platforms, Golden Paths, APIs, automation, and developer tooling and services using Python, Go, Java, or similar languages.
Build comprehensive observability using metrics, logs, traces, alerting, and automated remediation.
Explore and integrate Generative AI, AI Agents, MCP, and AI-assisted developer tooling into platform and engineering workflows.
Drive AIOps and intelligent automation for incident detection, troubleshooting, root-cause analysis, and operational optimisation.
Identify opportunities to improve platform scalability, reliability, performance, cost, and developer experience.
Collaborate across engineering, security, architecture, and operations teams and provide technical leadership on platform initiatives.
Build and standardise CI/CD, GitOps, Infrastructure-as-Code, and deployment automation.