AI Solutions Engineer

Position Overview

The AI Solutions Engineer designs, builds, and deploys AI‑driven solutions. This role takes validated concepts often originating from rapid prototypes or pilot programs and engineers them into scalable, secure, and operational systems. The focus is on applied AI: integrating machine learning, automation, and intelligent services into real‑world workflows within a public safety environment. It is a hands‑on, technical builder role that bridges experimentation and enterprise‑grade implementation.

Key Responsibilities

• Build & Productionize AI Solutions: design, develop, and deploy AI/ML solutions such as computer vision, natural language processing, predictive analytics, and automation; convert prototypes and proofs‑of‑concept into stable, scalable applications; develop APIs, services, and pipelines to integrate AI into existing systems.
• Engineer End‑to‑End Workflows: build data ingestion, preprocessing, model execution, and output delivery pipelines; integrate AI capabilities into law‑enforcement operational platforms; ensure reliability, performance, and maintainability of deployed solutions.
• Model Integration & Optimization: work with pre‑trained models, commercial AI services, or custom‑built models; fine‑tune, optimize, and evaluate models for accuracy and operational usefulness; implement monitoring for model performance and drift over time.

Minimum Requirements

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field (or equivalent combination of education and experience).
• Three (3) or more years of hands‑on experience building software or AI/ML solutions.
• Proficiency with Python and common AI/ML libraries (e.g., TensorFlow, PyTorch).
• Experience building APIs and integrating systems (REST, microservices).
• Understanding of data pipelines and cloud environments (Azure, AWS, or similar).

Preferences

• Experience with computer vision, natural language processing, or real‑time analytics.
• Familiarity with video analytics, sensor data, or geospatial data.
• Experience in public safety, government, or another regulated environment.
• Knowledge of MLOps practices (CI/CD for models, monitoring, versioning).

General Information

• Work Environment & Physical Demands: operates primarily in a professional office setting; standard use of computers, phones, printers, and related technical equipment; occasional ability to lift and carry up to 10 pounds.
• Position Type: Professional Staff, Full‑time, Exempt.
• Work Schedule: Typically Monday – Friday, 8:00 AM – 5:00 PM; hours may vary based on department business needs.