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Salary: USD 200,000 - 275,000 / annual
Peregrine Technologies, backed by leading Silicon Valley investors, builds an AI-enabled platform that transforms siloed data into operational intelligence for public safety organizations, government agencies, and private-sector institutions. The platform currently serves hundreds of customers across 30+ states and two countries, reaching over 125 million people.
You will join the engineering team as a Staff Software Engineer focused on Applied AI, taking a company-wide technical leadership role in building generative AI-powered features that unlock new ways for users to interact with the platform. Your scope encompasses complex challenges including scaling the platform to handle terabytes of data from diverse sources, efficiently querying and notifying users on this data in real-time, and optimizing search algorithms for fast results.
The engineering culture emphasizes ownership and collaboration. You will take full responsibility for major features while working closely with other engineers, the deployment team, and end users to iterate on solutions. The team values empathy, humility, and perseverance—seeing how people use the product is a priority.
The technical stack includes Python, Django, Celery, Airflow, and Kafka on the backend; React, Redux, and Mapbox on the frontend; PostgreSQL and Elasticsearch for data storage; machine learning models hosted in Bedrock and SageMaker; and AWS, Pulumi, Terraform, and Kubernetes for infrastructure.
REQUIREMENTS:
- Over 8 years of experience working with cross-functional software development teams
- Degree in Computer Science or related field, or equivalent professional experience
- Understanding of best practices for using generative AI responsibly, with bonus experience applying LLMs to enhance user experience
- Knowledge of how to train, deploy, integrate, and monitor machine learning models
- Experience shipping and iterating on production-grade software components professionally and/or in open-source
- Ability to write robust, well-tested, well-designed code that gets deployed to users frequently
- Strong best practices in modern software development and comfort navigating large codebases
- Located in San Francisco and open to working in office
