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Internship Backend Engineer Jobs in Texas (NOW HIRING)

Black Box

AI Engineer Intern - USA

Plano, TX · On-site

AI Engineer Intern - AI Center of Excellence (CoE) Location: Plano, Texas, USA Internship Duration: 6-12 months (12 months preferred) Company: Black Box Eligibility: Master's students with at least 6

Black Box

AI Intern - Dallas, TX

Plano, TX · On-site

AI Engineer Intern - AI Center of Excellence (CoE) Location: Plano, Texas, USA Internship Duration: 6-12 months (12 months preferred) Company: Black Box Eligibility: Master's students with at least 6

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Internship Backend Engineer information

What does an internship backend engineer do?

An Internship Backend Engineer assists in building and maintaining the server-side logic, databases, and APIs for web or mobile applications. Interns typically work alongside experienced engineers to write clean, efficient code, troubleshoot bugs, and help implement new features. They also learn about backend frameworks, security practices, and data management. The role is a valuable opportunity to gain hands-on experience in backend development and understand how large-scale systems operate.

What kinds of projects and responsibilities can I expect as an internship backend engineer?

As an Internship Backend Engineer, you can typically expect to work on tasks such as developing and maintaining APIs, writing and testing server-side logic, and collaborating with frontend engineers to integrate new features. You'll likely participate in code reviews, debugging sessions, and team stand-ups, giving you exposure to real-world software development practices. While you may start with smaller tasks, many teams encourage interns to gradually take on more complex projects as they gain confidence and skills. This hands-on experience is invaluable for learning best practices, understanding scalable architectures, and building a strong foundation for a future career in backend development.

What are the key skills and qualifications needed to thrive as an internship backend engineer, and why are they important?

To thrive as an Internship Backend Engineer, you need a solid understanding of server-side programming languages (such as Python, Java, or Node.js), databases, and basic software engineering principles, often supported by relevant coursework or personal projects. Familiarity with version control systems like Git, RESTful APIs, and cloud platforms such as AWS or Azure is typically required. Strong problem-solving skills, attention to detail, and effective communication help interns collaborate and learn quickly in team environments. These skills are crucial for contributing to robust, scalable backend systems and for adapting to the fast-paced demands of a software development team.

What are the most commonly searched types of Backend Engineer jobs in Texas?

The most popular types of Backend Engineer jobs in Texas are:

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For Internship Backend Engineer jobs in Texas, the most frequently searched job titles are:

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Cities in Texas with the most Internship Backend Engineer job openings:

Internship Backend Engineer jobs near you
Infographic showing various Internship Backend Engineer job openings in Texas as of August 2026, with employment types broken down into 24% Internship, and 76% Full Time. Highlights an 100% In-person job distribution.

AI Engineer Intern - USA

Black Box

Plano, TX • On-site

Part-time

Re-posted 10 days ago

Job description


AI Engineer Intern - AI Center of Excellence (CoE)
Location: Plano, Texas, USA
Internship Duration: 6-12 months (12 months preferred)
Company: Black Box
Eligibility: Master's students with at least 6 months remaining before graduation and prior professional experience in applied AI
Company Overview
Black Box Network Services is a leading global communications system integrator specializing in designing, sourcing, implementing, and managing complex technology solutions. As part of our strategic transformation, Black Box is expanding its AI Center of Excellence (CoE) to deliver enterprise-grade AI solutions across multiple business domains.
The AI CoE focuses on building scalable, secure, and production-ready AI systems, establishing best practices for enterprise AI adoption, and integrating AI capabilities into core business platforms.
Role Summary
As an AI Engineer Intern in the AI Center of Excellence (CoE), you will contribute to the design, development, and integration of applied AI solutions using pre-trained Large Language Models (LLMs), traditional machine learning techniques, and deterministic approaches.
This role offers hands-on experience building enterprise-grade Generative AI solutions across backend services, data pipelines, orchestration, and user-facing applications. Working closely with experienced AI engineers, you will contribute to real-world AI use cases integrated with platforms such as ServiceNow, SAP, Salesforce, and Azure services.
This internship is designed to strengthen applied AI engineering skills and prepare candidates for conversion into a full-time AI Engineer role.
Eligibility Requirements
  • Currently pursuing a Master's degree in Engineering or a related field (Computer Science, Artificial Intelligence, Data Science, or similar).
  • Must have at least 6 months remaining to complete the Master's program at the time of joining.
  • Must have a minimum of 2+ years of relevant professional experience between Bachelor's and Master's programs.
  • Prior experience must include applied AI / Machine Learning, with hands-on exposure to Generative AI use cases.
  • Available for a full-time, on-site internship for a minimum of 6-12 months (depending on academic program constraints).
Key Responsibilities
AI & Generative AI Development
  • Build and integrate AI solutions using pre-trained LLMs for conversational AI, summarization, and enterprise knowledge retrieval.
  • Implement RAG-based architectures connecting LLMs with structured and unstructured enterprise data.
  • Develop and test AI agents, traditional ML models, and deterministic logic for real-world use cases.
  • Contribute to AI orchestration using LangChain and workflow automation using n8n.
Full-Stack & Enterprise Integration
  • Build AI-enabled user interfaces and integrate them with backend services.
  • Develop and maintain backend APIs and services.
  • Integrate AI solutions with enterprise platforms such as ServiceNow, SAP, Salesforce, and Azure services.
Data, Testing & Deployment
  • Build and maintain data pipelines, including preprocessing and quality checks.
  • Support testing, debugging, deployment, and monitoring of AI services on Azure.
  • Document AI workflows, integrations, and solution lifecycle updates.
Learning & Collaboration
  • Collaborate with AI, data, and platform teams to deliver production-ready AI solutions.
  • Continuously learn and apply best practices in Generative AI, RAG patterns, and enterprise AI systems.
Required Technical Skills
  • Programming: Strong working knowledge of Python.
  • Applied AI / GenAI: Hands-on experience building or integrating ML or Generative AI solutions.
  • Generative AI: Practical experience with LLMs, prompt engineering, and/or RAG-based architectures.
  • Backend Development: Experience building APIs using FastAPI, Flask, or Node.js (TypeScript).
  • Frontend Development: Working experience building React-based user interfaces and integrating them with backend APIs.
  • Data Handling: Experience working with structured and unstructured data, including basic preprocessing or ETL.
  • APIs & Cloud: Experience consuming REST APIs and familiarity with cloud platforms (Azure preferred).
Required Prior Professional Experience
  • 2+ years of relevant professional experience between Bachelor's and Master's programs.
  • Experience in applied AI, machine learning, or software engineering with AI components.
  • Ability to translate AI concepts into working prototypes or production-ready solutions.
Required Soft Skills
  • Strong learning mindset, ownership, and clear communication with a structured problem-solving approach.
Preferred Skills / Experience
  • Familiarity with NLP concepts and foundational Generative AI models.
  • Awareness of responsible AI and basic AI governance concepts.
  • Exposure to Microsoft Power Platform or low-code automation tools.
About Black Box
Black Box is a leading technology solutions provider focused on accelerating customer success through innovation, ownership, transparency, and collaboration. With over 2,500 team members across 24 countries, Black Box delivers high-value solutions globally and is a wholly-owned subsidiary of AGC Networks.
Black Box is an equal opportunity employer.

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