Artificial Intelligence (AI) Engineer

Role: Artificial Intelligence (AI) Engineer

Duration: 12+ Months

Location: Austin, TX 78744 (This role requires onsite presence 4 5 days per week. Candidates must reside in the Austin area and be authorized to work in the U.S.)

Primary Skills: AI Engineer with AI/ML, Python, Cloud Platforms (AWS, Azure, Google Cloud Platform, OCI), DevOps, SQL (PostgreSQL, MySQL) and NoSQL/vector databases, Scripting (Bash, PowerShell) & CLI

Summary:

The Artificial Intelligence (AI) engineer will develop AI/ML proof-of-concept demonstrations and build new AI/ML solutions that scale with the client pipelines and workflows. The role will be embedded within the Traffic Technology team with the goal to develop AI/ML for Operational Technology that improves the safety and operations of the client roadway system. The AI engineer will work across teams such as Traffic Technology, ITD AI team, and TRF to gather business requirements, develop AI software, and demonstrate successful solutions to end-users.

Core Responsibilities

• Gather and document AI solution requirements from business stakeholders.
• Develop AI proof-of-concepts and transition successful prototypes into production systems.
• Design and implement scalable AI pipelines for enterprise applications.
• Train, fine-tune, and validate AI/ML models for optimal performance.
• Write clean, efficient software code and scripts for AI workflows.
• Conduct rigorous testing and quality assurance of AI models and outputs.
• Ensure compliance with organizational IT governance, security, and audit standards.

Stakeholder Engagement & Communication

• Act as liason between Traffic Technology team, business stakeholders, and automation developers.
• Facilitate requirements gathering and ensure clarity in AI solution design.
• Communicate progress, risks, and issues to project sponsors and leadership teams.

Delivery Excellence & Governance

• Ensure automation projects comply with the client IT governance, security, and audit requirements.
• Promote reusable components and standardized AI development practices.
• Conduct post-implementation reviews to capture lessons learned and improve delivery methods.

Team Coordination & Support

• Collaborate with data engineers, business analysts, and infrastructure teams.
• Provide guidance on AI best practices and assist in troubleshooting.
• Support knowledge sharing and continuous improvement within the team.

Minimum Yrs of Experience, Skills, and Qualifications

• Python 1-3+ years production experience, this is your primary language
• AI/ML Production - Built and deployed 1-3+ ML models serving real users, not just experiments
• Cloud Platforms - Experience with AWS, Azure, Google Cloud Platform, or OCI for deploying and managing ML workloads. We leverage AI/ML tools across all major cloud providers (Azure AI, AWS SageMaker/Bedrock, Google Cloud Platform Vertex AI, OCI AI Services)
• DevOps - Docker and Kubernetes experience
• Databases - SQL (PostgreSQL, MySQL) and NoSQL/vector databases
• Scripting - Proficient in both Bash and PowerShell for automation
• Command Line Interface (CLI) 1-3+ years production experience working in CLI terminal.

Preferred Skills and Qualifications

• CI/CD Experience: Azure DevOps, GitHub Actions, Jenkins, or similar automation pipelines
• Computer Vision: Production CV experience with PyTorch/TensorFlow, OpenCV, object detection, segmentation, or real-time inference
• Additional Languages: Go or Rust experience for performance-critical components
• Feature stores (Feast, Tecton) or advanced feature engineering
• Model optimization: quantization, pruning, knowledge distillation
• Edge deployment or resource-constrained model deployment
• Experiment frameworks for A/B testing ML models
• Contributions to open-source ML projects
• Real-time streaming data processing (Kafka, Kinesis)