Full Stack Engineer; Agentic AI

Work Location: The Woodlands, TX (4 days in office)

Education/Experience

Required:

5 years of professional software development experience using .NET, C#, and Python

• Our Client is seeking a Full Stack Software Engineer to build and support scalable enterprise applications, with a strong focus on backend services for conversational and voice AI.
• Applications consist of backend services, APIs, integrations, and modern web interfaces to deliver AI-powered and customer-facing solutions.
• The ideal candidate is comfortable owning work end-to-end, from design through production and support.

• Design, build, and support cloud-native solutions in AWS using secure and scalable architecture patterns.
• Develop backend microservices that power conversational and voice AI applications.
• Build modern user interfaces that create a positive customer experience
• Integrate applications with third-party APIs, SaaS platforms, telephony, and CCaaS/CPaaS platforms.
• Work with key components of voice AI applications, such as streaming audio, barge-in handling, retries, fallbacks, and transcript capture.
• Develop as part of an Agile team, utilizing CI/CD, automated testing, and IaC templates.
• Implement logging, metrics, alerting, and health checks to keep production services observable and reliable.
• Troubleshoot application and infrastructure issues across the stack.

• 5 years of professional software development experience using .NET, C#, and Python
• Bachelor's degree in Computer Science, IT, or related field - or equivalent work experience.
• Strong understanding of REST APIs, microservices, and application integration patterns.
• Experience with cloud services and container-based deployments (AWS-preferred).
• Experience with agentic AI development tools and frameworks.
• Proficiency with at least one relational database technology.
• Experience with React and/or Angular, Type Script, and modern frontend tooling.
• Familiarity with Git Hub Actions or comparable CI/CD tooling and automated testing practices.
• Experience with conversational or voice AI systems (e.g. streaming audio, turn-taking, LLM orchestration).
• Familiarity with voice AI evaluation metrics and frameworks
• Disciplined approach to security and compliance, including handling of PII, customer account data, secrets, least privilege, auditability, and PCI-sensitive boundaries.