What are the responsibilities and job description for the AI Engineer SDLC & Automation position at Maddisoft?
Job Details
Maddisoft has the following immediate opportunity, let us know if you or someone you know would be interested. Send in your resume ASAP. - U.S. Citizens and those authorized to work in the U.S. are encouraged to apply. Send in resume along with LinkedIn profile without which applications will not be considered. Call us NOW! ***Visa sponsorship is available for this position.*
Job Title: AI Engineer - SDLC & Automation
Location: Austin, Texas- Hybrid
Interview Type- In person /MS Teams
We are seeking an innovative AI Engineer to transform and optimize our Software Development Lifecycle (SDLC) through automation and advanced AI/ML capabilities. This role focuses on building internal AI-driven engineering solutions not supporting external AI product teams. The ideal candidate is passionate about automation, developer productivity, operational reliability, and applying AI/ML to solve engineering challenges at scale.
Key Responsibilities
- Design and implement AI/ML solutions to enhance SDLC processes, including:
- Developer experience and productivity
- Intelligent test management and predictive analytics
- Predictive infrastructure failure detection
- Agentic AI, MCP automation, and RAG-based workflows
- Intelligent alerting, noise reduction, and anomaly detection
- Automated incident classification & root-cause analysis
- CI/CD optimization using historical data
- GenAI-driven Infrastructure-as-Code (IaC)
- Other internal automation and innovation use cases
- Partner with Development, DevOps, Cloud, and Infrastructure teams to identify automation opportunities.
- Build automation tools and scripts to reduce manual effort and operational toil.
- Develop and maintain pipelines for training, deploying, and improving internal AI models.
- Create architecture and design documentation for AI-driven solutions.
- Ensure reliability, scalability, and performance of AI automation systems.
- Integrate AI capabilities into monitoring and observability platforms.
- Perform system analysis, troubleshooting, defect diagnosis, and performance tuning.
- Work in Agile Scrum environments and collaborate across engineering teams.
- Support GitHub Administration:
- Repository and branching strategy management
- Workflow automation with GitHub Actions (or similar CI/CD tools)
- Code quality, governance, and access control
- Other engineering duties as assigned.
Required Skills & Qualifications
- Bachelor s degree in Computer Science, Engineering, or equivalent.
- 3 years of experience in Software Development, Automation, or DevOps engineering.
- Strong background in cloud-native technologies (AWS, Azure, or Google Cloud Platform).
- Proficiency in automation/scripting Python preferred (Bash, PowerShell also useful).
- Solid understanding of CI/CD pipelines and DevOps tooling.
- Experience applying AI/ML techniques for real-world engineering challenges (classification, clustering, anomaly detection, etc.).
- Familiarity with ML frameworks: Scikit-learn, TensorFlow, PyTorch, etc.
- Strong understanding of monitoring, logging, and observability tools.
- Experience working in developer IDEs (Eclipse, IBM RAD, STS, etc.).
Preferred Skills
- Experience with predictive analytics, anomaly detection, and time-series forecasting.
- Knowledge of internal MLOps practices for model lifecycle management.
- Experience integrating AI models into DevOps and automation workflows.
- Familiarity with IaC tools (Terraform, Pulumi, CloudFormation).
- Experience with Hyper-V Virtual Machine Management.
- Asset and service account management experience.
- Experience using BMC Helix or similar ticketing systems.