Artificial Intelligence Engineer

Role: AI Engineer Location: Austin, TX Contract 529601510 We are seeking an AI Engineer to drive innovation in our SDLC processes using artificial intelligence and automation. This role is ideal for an engineer passionate about automation and applying AI/ML techniques to improve reliability, observability, and operational workflows. The focus of this role is not to support external AI/ML product teams, but to internally develop AI-driven solutions that optimize SDLC processes, reduce toil, and increase automation maturity across the organization. Key Responsibilities: Design and implement AI/ML models that improve SDLC processes in domains, such as: o Developer experience and productivity o Intelligent test management using data analytics and predictive techniques o Predictive infrastructure failure detection o Agentic AI, MCP implementation, and RAG techniques o Intelligent alerting and noise reduction o Automated incident classification and root-cause analysis o CI/CD optimization based on historical trends o Using GenAI for IaC o Any other innovative use-cases. Work closely with Development, DevOps, and Infrastructure teams to identify automation opportunities and pain points. Develop automation scripts and tooling to reduce manual tasks, operational efficiencies, and user experience. Build, deploy, and maintain pipelines to train and continuously improve AI models for DevOps use-cases. Collaborate with Infrastructure, Cloud, and DevOps teams to create architecture/design documents for proposed solutions. Ensure operational reliability, scalability, and performance of AI-driven automation tooling. Integrate AI solutions into monitoring. Experience with Agile Scrum and DevOps methodologies Experience working in Developer IDEs, such as Eclipse, IBM Rational Application Developer, STS, etc. Create technical and design documentation, as required Perform system analysis, troubleshooting, diagnosis and problem resolution. Analyze software for defects and performance tuning opportunities GitHub Administration: - Manage repositories, branching strategies, and access control. -Automate workflows using GitHub Actions or similar CI/CD tools. -Maintain code quality and integration processes. -Define and implement governance rules. Other duties as assigned. Required Skills & Qualifications: Bachelors degree in Computer Science, Engineering, or equivalent experience. 3+ years in Development/Automation roles. Strong background in cloud-native infrastructure (AWS, Azure, or GCP). Proficiency in automation and scripting (Python is preferred, Bash, etc.). Solid understanding of CI/CD pipelines Experience with cloud-native technologies Experience applying AI/ML techniques to solve engineering problems (e.g., anomaly detection, classification, clustering). Familiarity with Python machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch). Good understanding of monitoring, logging, and observability tooling. Preferred Skills: Experience with anomaly detection, predictive analytics, or time-series forecasting. Knowledge of MLOps practices (for internal AI models). Experience integrating AI solutions into DevOps toolchains and platforms. Familiarity with infrastructure as code (Terraform, Pulumi, CloudFormation). Some working experience with Hyper-V Virtual Machine Management Asset and service account management BMC Helix ticketing system II. CANDIDATE SKILLS AND QUALIFICATIONS Minimum Requirements: Candidates that do not meet or exceed the minimum stated requirements (skills/experience) will be displayed to customers but may not be chosen for this opportunity. Years Required/Preferred Experience 8 Years Required - Proven ability to administer GitHub Enterprise Cloud Proven ability to analyze and resolve complex issues Supporting and training end users on all levels. Hands-on experience with Continuous Integration Delivery models Hands-on experience with large development projects using Agile methodology