Careers

Responsibilities

• Understand stakeholder data needs and translate them into technical requirements.
• Build and manage dbt pipelines that transform raw logs into canonical datasets.
• Establish data integrity standards and SLAs for accurate, timely delivery.
• Develop dashboards and self-serve analytics tools for company-wide insights.
• Partner with Product and GTM teams from a data systems perspective.

Required Skills

• 5+ years in Analytics Data Engineering, Data Science, or Analytics roles.
• Strong SQL, Python, dbt, Airflow, GitHub, and multi-step ETL experience.
• Dashboarding experience with tools such as Hex.
• Full-stack mindset, strong ownership, and ability to work in ambiguity.

Key Responsibilities

• Design, test, and optimize system prompts and feature-specific prompts.
• Build and maintain evaluation suites for model quality and consistency.
• Partner with product, research, and safeguards teams for feature quality and safety.
• Support model launches and catch regressions before user impact.
• Improve prompt and evaluation tooling, and mentor engineers on best practices.

Qualifications

• 5+ years of software engineering experience with Python or similar languages.
• Experience with LLMs, prompt engineering, and AI evaluation methods.
• Strong communication, version control, CI/CD, and modern engineering practices.
• Preferred: Claude/frontier models, ML/NLP, A/B testing, AI safety, and ML workflow tooling.

Responsibilities

• Procure and maintain Kubernetes, storage, Hadoop/object store, and job scheduler capabilities.
• Support ADT table creation, modification, replication, and cleanup for data products and data science.
• Create scripts for onboarding/offboarding data products to access modules like ADAM/Papyrus.
• Own namespace administration, CI/CD, GitHub branching, PR, and deployment processes.
• Enable notebooks, compute, plugins, data governance access, and platform integrations.

Skills

• HDFS, ObjectStore, containers, Kubernetes, Jenkins, Bash/Python scripting, Airflow, Git, and GitHub Enterprise.
• Preferred: Iceberg tables, Parquet, Trino, Jupyter Notebook, access control principles, and Hive metastores.

Key Responsibilities

• 5+ years of DevOps/SRE and migration experience.
• Support telemetry and observability stacks in Kubernetes environments.
• Develop Python scripts and tools for automation, monitoring, and support.
• Configure, monitor, and troubleshoot Grafana, Prometheus, Loki, and related tools.
• Collaborate with DevOps, SRE, and development teams on reliability and performance.

Required Skills

• Kubernetes, Python, Docker, CI/CD, Linux, Git workflows, logging, and tracing.
• AWS/EKS, cloud networking, Unix shell scripting, DevOps automation, and monitoring.
• Preferred: Cilium, Pulumi, Terraform, Helm, Spinnaker, AWS, GCP, Azure, and performance tuning.

Location

• Austin / SCV

Responsibilities

• Procure and maintain infrastructure capabilities including Kubernetes, Hadoop storage, and object store.
• Maintain and support job schedulers required for running data jobs.
• Support ADT data table creation, modification, replication, and cleanup for data products or data science.
• Create scripts and ensure onboarding/offboarding of data products to access modules such as ADAM/Papyrus.
• Own namespace administration, CI/CD, GitHub branching, PR processes, and deployment pipelines using Rio.
• Set up access controls and deployment configuration by environment so data pipelines can run across dev, stage, and prod.
• Create job workflows on schedulers and enable alerts through Slack, email, and related channels.
• Enable notebooks, compute, plugins, and Git processes for exploratory SQL/Python analysis and ad hoc notebook pipelines.
• Support data access for data science teams following prescribed governance practices.
• Work with Amp Platform capabilities such as Lakehouse and Snowflake.

Skills

• Strong understanding of HDFS, ObjectStore, containers, Kubernetes, Jenkins, Bash/Python scripting, Airflow job scheduler, Git, and GitHub Enterprise.

Ideal Qualifications

• Working knowledge of Iceberg tables, Parquet files, Trino, Jupyter Notebook, access control principles, and Hive metastores.

Location

• Hyderabad, Bangalore

Key Responsibilities

• Demonstrate success working both independently and collaboratively within a team.
• Lead deployment of solutions and debug issues on customer-hosted infrastructure.
• Ensure all operational tools are implemented according to best practices.
• Work comfortably in an onsite/offshore model.

Required Skillset

• At least 5 years of AWS and EKS infrastructure SRE/Operations experience.
• Proficiency with AWS services such as S3, IAM, EKS, EC2, and Kubernetes deployment and pod monitoring.
• Deep knowledge of Kubernetes internals and components.
• Experience with Python or Shell scripting for automation.
• AWS networking knowledge including VPC, NAT, DNS, gateways, and related components.
• Strong DevOps automation experience with CI/CD tools such as ArgoCD or FluxCD.
• Infrastructure-as-code experience in AWS using Terraform preferred, or CloudFormation.
• Working experience creating dashboards in Splunk and Grafana.

Location

• Cupertino, Raleigh NC, or London

Skills

• Strong Kotlin and Java experience.

Project Context

• Re-architect Apple's core provisioning platform, which transforms user credentials into Wallet passes.
• Modernize an outdated, complex, monolithic system with scalability and maintainability challenges.
• Build a domain-driven, layered architecture to unify provisioning across Wallet offerings.
• Create a flexible, scalable, and consistent platform for faster development velocity and stronger resilience.
• Support both Platform-as-a-Service and custom composition models for diverse integration needs.