AI Engineer

City: Austin

State: Texas

Neos is seeking an AI Engineer for a contract role with our client in Austin, TX.

*** HYBRID – ONLY CANDIDATES CURRENTLY RESIDING IN THE AUSTIN, TX AREA WILL BE CONSIDERED***

The primary work location will be: 1609 Centre Creek Dr., Austin, Texas 78754

Position will be 3 days remote with 2 days (Tuesdays and Fridays) required to be onsite.

*** Subject to change per manager***

Interviews will be conducted both via Teams and onsite in Austin.

No calls, no emails, please respond directly to the “apply” link with your resume and contact details.

Develops software solutions by studying information needs, conferring with users, and studying systems flow, data usage, and work processes. Investigates problem areas. Prepares and installs solutions by determining and designing system specifications, standards, and programming.

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.

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, Dev Ops, 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 Dev Ops use‑cases.

Collaborate with Infrastructure, Cloud, and Dev Ops 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 Dev Ops 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, troubleshoot, diagnose, and resolve problems. Analyze software for defects and performance tuning opportunities.

• Manage repositories, branching strategies, and access control.
• Automate workflows using Git Hub Actions or similar CI/CD tools.
• Maintain code quality and integration processes.
• Define and implement governance rules.
• Other duties as assigned.
• 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 Google Cloud Platform).
• Proficiency in automation and scripting (Python 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, Tensor Flow, PyTorch).
• Good understanding of monitoring, logging, and observability tooling.

• Experience with anomaly detection, predictive analytics, or time‑series forecasting.
• Knowledge of MLOps practices (for internal AI models).
• Experience integrating AI solutions into Dev Ops tool chains and platforms.
• Familiarity with infrastructure as code (Terraform, Pulumi, Cloud Formation).
• Some working experience with Hyper‑V Virtual Machine Management.
• Asset and service account management.
• BMC Helix ticketing system.

• 8 years required – Proven ability to administer Git Hub Enterprise Cloud.
• 8 years required – Proven ability to analyze and resolve complex issues.
• 8 years required – Supporting and training end users on all levels.
• 8 years required – Hands‑on experience with Continuous Integration Delivery models.
• 3 years preferred – Hands‑on experience with large development projects using Agile methodology.