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GenAI Software Engineer

United StatesHybridFull TimePosted 1 month agoVisa sponsorship available

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Software Engineer – AI & Platform Engineering

Location: Dallas, TX (Hybrid)

• Competitive base salary + performance bonus

• 100% company-paid benefits

Overview

We are hiring a Software Engineer to help build and enhance platforms that support both core infrastructure and emerging AI-driven capabilities.

This role blends application development with platform engineering, focusing on integrating intelligent workflows into existing systems while maintaining high standards for performance, reliability, and usability. The ideal candidate has a strong engineering foundation and experience working on systems that incorporate or support AI/ML functionality.

Key Responsibilities

Application & Platform Development

• Design and deliver scalable services and applications that support platform and infrastructure needs

• Build internal tools that streamline automation, improve system efficiency, and enhance developer workflows

• Write clean, maintainable code aligned with modern engineering best practices

AI Enablement

• Contribute to the integration of AI/ML capabilities within broader system architecture

• Identify opportunities to leverage emerging AI technologies to improve platform capabilities

System Reliability & Enhancement

• Support ongoing platform stability through issue resolution, enhancements, and continuous improvements

• Participate in agile development processes, including sprint planning and retrospectives

Required Experience

• Strong experience developing software in production environments

• Proficiency in Python; additional experience with Go or .NET is beneficial

• Hands-on experience with containerized environments and orchestration platforms (e.g., Docker, Kubernetes)

• Familiarity with cloud environments such as AWS or Azure

• Solid understanding of testing practices and maintainable code design

• Experience working within agile teams and iterative development cycles

Preferred Experience

• Exposure to AI/ML concepts or experience working on systems that incorporate intelligent workflows

• Experience integrating external services, APIs, or data-driven components into applications

• Familiarity with monitoring, logging, or telemetry systems

• Experience building or supporting microservices-based architectures in cloud environments

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