Software Engineer 3

Title : Software Engineer 3

Duration : 01 / 05 / 2026 - 08 / 31 / 2026

Location : 1609 Centre Creek Dr., Suite 200 Austin, TX

Work Hours : Monday to Friday 8 : 00 AM to 5 : 30 PM (CST)

Position : Hybrid

Key Responsibilities :

• Design and implement AI / ML models that improve SDLC processes in domains, such as :
• Developer experience and productivity
• Intelligent test management using data analytics and predictive techniques
• Predictive infrastructure failure detection
• Agentic AI, MCP implementation, and RAG techniques
• Intelligent alerting and noise reduction
• Automated incident classification and root-cause analysis
• CI / CD optimization based on historical trends
• Using GenAI for IaC
• 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 :

Required Skills & Qualifications :

Bachelor s 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

Required

Proven ability to administer GitHub Enterprise Cloud

Required

Proven ability to analyze and resolve complex issues

Required

Supporting and training end users on all levels.

Required

Hands-on experience with Continuous Integration Delivery models

Preferred

Hands-on experience with large development projects using Agile methodology