Senior AI Specialist - Hybrid

Job Title:

Senior AI Specialist

Location:

Pontiac, MI

Contract:

6 months (possible to extend). Hybrid: 2 days onsite, 3 days remote.

The AI Specialist is responsible for designing, developing, and deploying artificial intelligence and machine learning solutions that enhance business processes, improve decision making, and drive innovation. This role works closely with cross-functional teams to identify use cases, gather requirements, and implement AI‑powered applications. Core responsibilities include data preprocessing, model selection, training, validation, and deployment, as well as staying current with emerging AI research and industry trends.

A major focus of this assignment is building a natural language search solution that allows law enforcement and authorized users to query CLEMIS data conversationally, replacing complex SQL queries and traditional search interfaces.

The specialist will integrate multiple public safety datasets, migrate and transform data into AWS, ensure CJIS‑compliant security, and implement advanced RAG capabilities using modern AI models within a fully cloud‑hosted architecture.

Experience designing, developing, and deploying AI/ML solutions in production environments.

Ability to build natural language query systems that translate everyday language into structured data retrieval.

2–3 years of experience with Public Safety applications such as CAD, RMS, and FRMS, with strong understanding of dataset structures and relationships.

Experience working with CLEMIS or similar law enforcement data systems.

Ability to work with existing CLEMIS datasets, including People, Identifiers, and Incidents/Offenses.

Familiarity with predictive analytics using RMS data.

Experience extracting data from on‑prem Oracle and SQL Server databases and migrating it to AWS Cloud.

Strong skills in data transformation, including masking of sensitive information (CJIS, PII, etc.).

Experience storing data in vector databases optimized for AI/ML workloads (e.g., Pinecone).

Hands‑on experience enabling RAG (Retrieval Augmented Generation) capabilities, ideally with AWS Bedrock.

Ability to work with industry‑standard AI models such as Claude, AWS Titan, or Nova.

Experience deploying end‑to‑end AI solutions fully hosted in AWS Cloud.