AI DevOps Automation Engineer (Python, GitHub, Cloud – SDLC, RAG, MLOps) at ACS Consultancy Services

Job Title : AI DevOps Automation Engineer (Python GitHub Cloud SDLC RAG MLOps) Location: Austin TX (Hybrid -Local Candidates only) We are currently seeking candidates who meet the following qualification Mandatory Qualifications Bachelors degree in Computer Science Engineering or equivalent experience Proven ability to administer GitHub Enterprise Cloud Strong experience analyzing and resolving complex technical issues Experience supporting and training end users at all levels Hands-on experience working with Continuous Integration and Continuous Delivery models Background in cloud-native infrastructure (AWS Azure or GCP) Proficiency in automation and scripting (Python preferred; Bash or similar also accepted) Strong understanding of CI/CD pipelines and cloud-native technologies Experience applying AI/ML techniques for engineering use cases (anomaly detection clustering classification etc.) Familiarity with ML frameworks such as Scikit-learn TensorFlow or PyTorch Good understanding of monitoring logging and observability tooling Experience working with developer IDEs (Eclipse IBM RAD STS etc.) Preferred Qualifications Experience with anomaly detection predictive analytics or time-series forecasting Knowledge of MLOps principles for internal AI models Experience integrating AI solutions into DevOps toolchains Familiarity with IaC tools such as Terraform Pulumi or CloudFormation Experience with Hyper-V virtual machine management Asset and service account management experience Exposure to BMC Helix ticketing systems Experience working on large development projects using Agile methodology Responsibilities Design and implement AI/ML models to enhance SDLC processes in areas such as: Developer productivity and experience Intelligent test management using analytics and predictive techniques Predictive infrastructure failure detection Agentic AI MCP implementation and RAG methods Intelligent alerting and noise reduction Automated incident classification and root-cause analysis CI/CD optimization based on historical data Generative AI for Infrastructure-as-Code Other innovative automation use cases Work closely with Development DevOps and Infrastructure teams to identify automation opportunities and technical challenges. Develop automation scripts and tools to reduce manual effort and improve operational efficiency. Build deploy and maintain pipelines to train and continuously improve AI models supporting DevOps processes. Collaborate with Cloud Infrastructure and DevOps teams to develop architecture and design documents. Ensure reliability scalability and performance of AI-driven automation tools. Integrate AI solutions into monitoring and observability systems. Perform system analysis troubleshooting performance tuning and defect identification. Create documentation including technical designs workflows and operational guides. GitHub Administration: Manage repositories branching strategies and access controls Automate workflows using GitHub Actions or other CI/CD tools Maintain code quality and integration processes Define and enforce governance rules Support Agile Scrum and DevOps methodologies. Other duties as assigned. If you meet these qualifications please submit your application via link provided in Linkedin. Kindly do not call the general line to submit your application. Key Skills Continuous Integration,APIs,Automotive software,Test Cases,Electrical Engineering,Junit,Distributed Control Systems,Testng,Java,Test Automation,Programmable Logic Controllers,Selenium Employment Type : Full Time Experience: years Vacancy: 1