Senior AI Engineer

TL;DR

Senior AI Engineer (Python/TypeScript/AWS): Building scalable, cloud-native AI infrastructure and machine learning services for digital investigation workflows with an accent on real-time inference, orchestration, and observability. Focus on researching forensic-data algorithms, integrating LLM services, and designing reliable deployments across AWS and Kubernetes environments.

Location: Remote within the United States; U.S. citizenship required.

Company

Digital investigation and forensic technology company providing AI-powered solutions for public safety organizations, intelligence agencies, and businesses.

What you will do

• Design and implement features for AWS-based AI solutions, including job orchestration, manifest generation, and API integrations.
• Develop and maintain CI/CD pipelines with GitHub Actions, CDK, and AWS services such as SageMaker, Lambda, and Bedrock.
• Research and prototype machine learning algorithms that transform forensic data into investigation leads, evidence, and intelligence insights.
• Build and evaluate data-driven applications and take projects from initial research through proof-of-concept development.
• Improve code quality, testing, observability, dashboards, and monitoring across AI services.
• Collaborate with cross-functional teams and troubleshoot deployments in broader investigation workflows and runtime environments.

Requirements

• Strong proficiency in Python and TypeScript, including API development and cloud-native architectures.
• Hands-on experience with AWS services, particularly SageMaker and Lambda.
• Experience with PyTorch, Pandas, NumPy, and machine learning data-processing tools.
• Familiarity with GitHub workflows, secrets management, secure deployments, Amazon EKS, and Kubernetes.
• Experience with GenAI infrastructure, semantic caching, and LLM integration.
• U.S. citizenship and the ability to work remotely from the United States.

Culture & Benefits

• Work on AI-powered digital investigation and intelligence products.
• Collaborate within a heterogeneous, multidisciplinary research environment.
• Contribute to cloud, on-premises, and hybrid investigation deployments.
• Combine analytical research, experimental prototyping, and production engineering.