Software Dev Engineer, AWS Identity Analytics Platform
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Job Location:
Seattle, OR - USA
Monthly Salary:
Not Disclosed
Posted on:
Yesterday
Vacancies:
1 Vacancy
Department:
Job Summary
AWS Identity Analytics is reimagining how identity data is understood acted on and used to protect customers at scale. We build an AI-driven analytics platform that turns 50 PB of raw logs and metrics into proactive actionable insights for AWS Identity leadership and core service teams including IAM and STS. AWS teams across the organization also rely on our platform for impact analysis related to AWS Auth.
Our platform is the foundation on which everything else stands: ingesting petabyte-scale data from dozens of Identity services transforming it into structured queryable intelligence and serving it reliably to the ML models LLM agents and dashboards that our customers act on every day.
Are you excited by the prospect of building AI-powered solutions that let stakeholders access insights without needing to understand how the underlying data is organized or connected Do you want to work on petabyte-scale data processing enrichment and querying engines Do you want to work on a platform that directly shapes how AWS Identity services evolve influencing decisions that affect hundreds of millions of customers globally Do you thrive in ambiguous fast-paced environments where your engineering work drives measurable business outcomes
As a Software Development Engineer on the Identity Analytics team you will own the data platform infrastructure that makes our AI and analytics capabilities possible. You will design and operate the ingestion transformation and serving pipelines that feed our ML models and LLM-powered agents. You will be the engineering partner to our Applied Scientist translating research prototypes into production-grade systems that run reliably at scale. What makes this role distinct is the combination of deep platform engineering with direct scientific impact: the pipelines you build and the infrastructure you operate determine the quality freshness and reliability of every insight our customers receive.
Key job responsibilities
Design build and operate scalable data ingestion transformation and loading pipelines that process petabyte-scale Identity logs metrics and policy data from IAM STS and other AWS Identity services using services such as AWS Glue EMR Spark Athena S3 and Redshift.
Own the productionization lifecycle for ML models developed by the Applied Scientist: package deploy monitor and maintain models in production environments using SageMaker ECS and EKS ensuring reliability latency and scalability meet production standards.
Build and maintain the feature engineering infrastructure that transforms raw Identity data into structured datasets ready for ML training evaluation and inference.
Drive platform resilience and operational excellence designing for failure building robust monitoring and alerting reducing operational load through automation and ensuring the platform scales automatically to the demands of incoming data.
Partner with the Applied Scientist BIEs and product managers to understand analytical requirements design data models that support both current and future use cases and ensure the platform evolves ahead of customer needs.
Identify and build onboarding capabilities that reduce the time it takes for new Identity service teams to integrate their data into the platform and begin consuming insights.
Contribute to the teams technical direction by participating in design reviews raising the engineering bar through code reviews and bringing a systems-thinking perspective to how the platform scales over the next three to five years.
- 3 years of non-internship professional software development experience
- 2 years of non-internship design or architecture (design patterns reliability and scaling) of new and existing systems experience
- 1 years of designing and developing large-scale multi-tiered multi-threaded embedded or distributed software applications tools systems and services using: C# C Java or Perl experience
- Bachelors degree or foreign equivalent in Computer Science Engineering Mathematics or a related field
- 3 years of full software development life cycle including coding standards code reviews source control management build processes testing and operations experience
- Bachelors degree in computer science or equivalent
- Knowledge of Machine Learning and LLM fundamentals including transformer architecture training/inference lifecycles and optimization techniques
- Experience developing deploying and managing AI products at scale
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Our platform is the foundation on which everything else stands: ingesting petabyte-scale data from dozens of Identity services transforming it into structured queryable intelligence and serving it reliably to the ML models LLM agents and dashboards that our customers act on every day.
Are you excited by the prospect of building AI-powered solutions that let stakeholders access insights without needing to understand how the underlying data is organized or connected Do you want to work on petabyte-scale data processing enrichment and querying engines Do you want to work on a platform that directly shapes how AWS Identity services evolve influencing decisions that affect hundreds of millions of customers globally Do you thrive in ambiguous fast-paced environments where your engineering work drives measurable business outcomes
As a Software Development Engineer on the Identity Analytics team you will own the data platform infrastructure that makes our AI and analytics capabilities possible. You will design and operate the ingestion transformation and serving pipelines that feed our ML models and LLM-powered agents. You will be the engineering partner to our Applied Scientist translating research prototypes into production-grade systems that run reliably at scale. What makes this role distinct is the combination of deep platform engineering with direct scientific impact: the pipelines you build and the infrastructure you operate determine the quality freshness and reliability of every insight our customers receive.
Key job responsibilities
Design build and operate scalable data ingestion transformation and loading pipelines that process petabyte-scale Identity logs metrics and policy data from IAM STS and other AWS Identity services using services such as AWS Glue EMR Spark Athena S3 and Redshift.
Own the productionization lifecycle for ML models developed by the Applied Scientist: package deploy monitor and maintain models in production environments using SageMaker ECS and EKS ensuring reliability latency and scalability meet production standards.
Build and maintain the feature engineering infrastructure that transforms raw Identity data into structured datasets ready for ML training evaluation and inference.
Drive platform resilience and operational excellence designing for failure building robust monitoring and alerting reducing operational load through automation and ensuring the platform scales automatically to the demands of incoming data.
Partner with the Applied Scientist BIEs and product managers to understand analytical requirements design data models that support both current and future use cases and ensure the platform evolves ahead of customer needs.
Identify and build onboarding capabilities that reduce the time it takes for new Identity service teams to integrate their data into the platform and begin consuming insights.
Contribute to the teams technical direction by participating in design reviews raising the engineering bar through code reviews and bringing a systems-thinking perspective to how the platform scales over the next three to five years.
- 3 years of non-internship professional software development experience
- 2 years of non-internship design or architecture (design patterns reliability and scaling) of new and existing systems experience
- 1 years of designing and developing large-scale multi-tiered multi-threaded embedded or distributed software applications tools systems and services using: C# C Java or Perl experience
- Bachelors degree or foreign equivalent in Computer Science Engineering Mathematics or a related field
- 3 years of full software development life cycle including coding standards code reviews source control management build processes testing and operations experience
- Bachelors degree in computer science or equivalent
- Knowledge of Machine Learning and LLM fundamentals including transformer architecture training/inference lifecycles and optimization techniques
- Experience developing deploying and managing AI products at scale
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience qualifications and location. Amazon also offers comprehensive benefits including health insurance (medical dental vision prescription Basic Life & AD&D insurance and option for Supplemental life plans EAP Mental Health Support Medical Advice Line Flexible Spending Accounts Adoption and Surrogacy Reimbursement coverage) 401(k) matching paid time off and parental leave. Learn more about our benefits at WA Seattle - 143700.00 - 194400.00 USD annually
Required Experience:
IC
Key Skills
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