Senior AI Platform Engineer

STRATEGIC STAFFING SOLUTIONS (S3) HAS AN OPENING!
 

Senior AI Platform Engineer
Detroit, MI (Hybrid/Onsite Tues-Thurs)
W2 contract role
12 Months then eligible for Contract renewal

Role Overview

We are seeking a Senior AI Platform Engineer to join our Advanced Analytics team and help transform analytical, machine learning, and Generative AI solutions into secure, scalable, production-ready applications.

Key Responsibilities

• Partner with Data Scientists, Analytics professionals, and business stakeholders to productionize AI, ML, and Generative AI solutions.
• Translate analytical and AI prototypes into scalable, maintainable software applications.
• Develop production-quality Python applications, APIs, services, and integration components.
• Design integrations between AI solutions and enterprise applications, data sources, APIs, and downstream systems.
• Establish reusable engineering patterns for AI and analytics solutions.
• Build and maintain data ingestion and integration pipelines supporting analytics and AI applications.
• Develop and maintain ETL/ELT processes to acquire, transform, validate, and prepare data for analytical and AI use cases.
• Integrate data from APIs, databases, files, enterprise applications, and other source systems.
• Design reliable, maintainable data workflows appropriate for application and analytical requirements.
• Design, deploy, and support AI and analytics applications within Microsoft Azure.
• Work with Azure Functions, Azure App Service, Azure Container Apps, Azure Storage, Azure Key Vault, Azure AI services, Azure AI Foundry, Azure AI Search, Azure Monitor, and related Azure resources.
• Understand Azure identity, authentication, authorization, networking, security, and resource-management concepts.
• Work comfortably in Linux-based development and runtime environments.
• Demonstrate practical Linux system administration knowledge, including processes, services, permissions, networking, package management, shell scripting, logs, and system troubleshooting.
• Troubleshoot application and environment issues across local Linux and cloud-hosted environments.
• Design and implement CI/CD pipelines using GitHub Actions to automate testing, building, and deployment.
• Automate movement of applications from development through test and production environments.
• Apply MLOps practices across the lifecycle of machine learning and AI applications from development through production.

Minimum Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent practical experience.
• 5+ years of experience in software, data, AI/ML, cloud, or platform engineering.
• Strong Python and SQL skills, with experience building production-grade applications and data solutions.
• Hands-on experience designing and building data ingestion, ETL/ELT pipelines, and scalable data engineering solutions to support analytics, AI/ML, and enterprise applications.
• Hands-on experience with DevOps and MLOps, including CI/CD, GitHub Actions, deployment automation, monitoring, and operational support.
• Experience developing and integrating REST APIs and enterprise applications.
• Hands-on experience deploying applications and services on Microsoft Azure.
• Experience with Docker, Podman, or similar container technologies.
• Strong Linux administration, troubleshooting, and command-line experience.

*Beware of scams. S3 never asks for money during its onboarding process