Stealth AI Startup (Policing)
Full-Stack / Cloud Engineer: Workflow, Systems & MLOps
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Our Aim
Our aim: to build real-world AI for safety- and privacy-critical settings, specifically policing. For police to serve people in a transparent and consensus-based way is demanding for many reasons. Lack of good interactive tools should not be among their challenges.
Focus of This Role
Build and maintain the internal backbone connecting our API, event-driven data pipelines, cloud infrastructure, and production ML models, spanning both AWS-hosted and on-premises deployments. Working with our head of integration in a multiple-hat role spanning full stack engineering, infra, and ML systems.
We're looking for a senior engineer who has learned the hard way: someone with real production ownership under their belt, startup scar tissue, and the instinct to get in and build. You'll own on-prem deployment end-to-end, contribute to our internal cloud infrastructure, and develop the broader product.
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Tech Stack
- Backend: Node, NestJS, Typescript, Drizzle.
- Frontend: React, Vite, Tanstack, Zustand.
- Databases: PostgreSQL, Redis/Valkey, Vector databases.
- IaC: Pulumi Typescript.
- AWS: ECS, Lambda, Kinesis, Aurora, S3, KMS, Cognito, CloudFront, ALB, GuardDuty, SecurityHub, SageMaker.
- Python: For Lambda handlers, ML inference glue, data processing.
Must-Have
- Production deployment experience and infrastructure as code.
- Experience with regulated data (law enforcement, healthcare, legal tech, or government), including data classification, audit trails, and access control patterns in practice.
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Nice-To-Have
- AWS SageMaker - training pipelines, model registry, endpoint deployment, or equivalent on another cloud (Vertex AI, Azure ML).
- Experience in dual deployment environments shipping the same application to both managed cloud and on-prem environments.
- Experience integrating with external hardware or edge-device APIs over cloud.
- Familiarity with CE/CE+ or security-conscious development in government/law enforcement contexts.
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