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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # DevOps Engineer - **Company:** Robotics Technologies LLC - **Location:** Atlanta, GA, United States - **Experience:** Starter - **Contract:** Temporary contract - **Skills:** A/B Testing, Artificial Intelligence, Amazon Web Services, Computer Vision, Microsoft Azure, Bash Shell, Command-Line Interface, Cloud Computing, Program Optimization, Databases, Continuous Integration, DevOps, Github, IT Management, Python (Programming Language), PostgreSQL, Machine Learning, MySQL, NoSQL, Object Detection, OpenCV, Open Source Technology, Windows PowerShell, Tensorflow, SQL Databases, Data Streaming, Data Processing, Scripting, Google Cloud, Enterprise Software Applications, Feature Engineering, Pytorch, Delivery Pipeline, AI Platforms, Apache Kafka, Machine Learning Operations, Software Coding, Oracle Cloud Infrastructure, Automation Anywhere, Docker, Jenkins - **Published:** June 20, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=53640afa375309cf ## About the Role * 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, GCP, or OCI for deploying and managing ML workloads. We leverage AI/ML tools across all major cloud providers (Azure AI, AWS SageMaker/Bedrock, GCP 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) ## Description The Artificial Intelligence (AI) engineer will develop AI/ML proof-of-concept demonstrations and build new AI/ML solutions that scale with 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 TxDOT 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 liaison 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 TxDOT's 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. ## Related Videos - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [MySQL Protocol Features You Should Be Aware Of](https://www.wearedevelopers.com/videos/100267-mysql-protocol-features-you-should-be-aware-of) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Tomorrow's cloud data platforms - fully managed database-as-a-service (DBaaS)](https://www.wearedevelopers.com/videos/254-tomorrow-s-cloud-data-platforms-fully-managed-database-as-a-service-dbaas) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Dev Digest 137 - AI'm not sure about this](https://www.wearedevelopers.com/magazine/485-dev-digest-137-ai-m-not-sure-about-this) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)