Are you looking to start your career in Artificial Intelligence, AI Agents, and Machine Learning? The AI Engineering Internship at Unisys is a strong opportunity for students who want practical experience building AI solutions for enterprise environments.
This AI Engineering Internship is a 9-month program based in Bengaluru. Interns will work with experienced domain experts to convert AI pipelines into functional prototypes and help transform promising solutions into production-ready systems.
- 1 AI Engineering Internship 2026 โ Overview
- 2 About the AI Engineering Internship
- 3 What Will You Do as an AI Engineering Intern?
- 4 Building AI Agents
- 5 Eligibility Criteria
- 6 Skills Required
- 7 Programming & Problem-Solving Skills
- 8 Cloud Knowledge
- 9 GitHub & Personal Projects
- 10 Internship Duration & Work Model
- 11 Career Benefits of the AI Engineering Internship
- 12 Why Apply for This AI Engineering Internship?
- 13 Final Thoughts
AI Engineering Internship 2026 โ Overview
| Job Details | Information |
|---|---|
| Company | Unisys |
| Role | AI Engineering Intern |
| Location | Bangalore, Karnataka |
| Job Type | Full-Time Internship |
| Duration | 9 Months |
| Experience | Internship / Student Opportunity |
| Education | Final-year B.Tech / M.Tech |
| Specialization | AI/ML, Computer Science or related field |
| Work Model | Work From Office |
| Job ID | REQ574279 |
About the AI Engineering Internship
The AI Engineering Internship focuses on practical AI engineering rather than only theoretical machine learning concepts.
Selected interns will work with domain experts to develop AI pipelines, build prototypes, test AI agents, and improve solutions so they can eventually be deployed in enterprise environments.
The role is particularly suitable for students who enjoy building, testing, debugging, and improving real software systems.
What Will You Do as an AI Engineering Intern?
During the AI Engineering Internship, you will contribute to different stages of AI solution development.
AI Pipeline Development
You will collaborate with experienced professionals to convert existing AI pipelines into working prototypes.
This can involve:
- Understanding existing AI workflows
- Implementing functional prototypes
- Testing AI solutions
- Debugging technical problems
- Improving system reliability
- Preparing solutions for production environments
Building AI Agents
One of the key areas of this AI Engineering Internship is AI agent development.
Interns will work on:
- AI agents
- Agent orchestration
- AI tools
- Agent evaluation
- Testing frameworks
- Guardrails
- Supporting AI harnesses
The goal is to make AI systems more reliable, testable, maintainable, and suitable for enterprise use.
Eligibility Criteria
According to the job description, candidates should be pursuing their final year of B.Tech in Artificial Intelligence & Machine Learning (AI/ML) and are expected to graduate in 2027 or 2028.
The description also mentions candidates pursuing or recently completing an M.Tech in Computer Science, AI/ML, or a related field.
Candidates should carefully verify their eligibility against the specific application requirements before applying.
Skills Required
| Skill Area | Expected Knowledge |
|---|---|
| AI | Artificial Intelligence fundamentals |
| AI Agents | Agents, orchestration, tooling |
| Evaluation | AI testing and evaluation |
| Guardrails | AI safety and reliability concepts |
| Programming | Strong programming fundamentals |
| Debugging | Practical troubleshooting skills |
| Cloud | AWS, Azure or GCP exposure is a plus |
| Development | Production-oriented software engineering |
| Collaboration | Cross-functional teamwork |
Programming & Problem-Solving Skills
A strong foundation in programming is important for the AI Engineering Internship.
Candidates should be comfortable with:
- Programming fundamentals
- Logical problem-solving
- Debugging
- Writing maintainable code
- Testing
- Understanding software workflows
The company is looking for candidates with a hands-on and empirical approach to solving technical problems.
Cloud Knowledge
Cloud experience is not necessarily mandatory, but it can be an advantage.
Candidates with exposure to platforms such as:
- AWS
- Microsoft Azure
- Google Cloud Platform
may have an additional advantage when working on enterprise AI systems.
Basic understanding of cloud deployment and application hosting can also help candidates understand how AI solutions operate outside a local development environment.
GitHub & Personal Projects
One of the useful aspects of this AI Engineering Internship is that candidates can showcase their practical work.
Public projects and GitHub repositories are listed as a nice-to-have.
Students can strengthen their profile by building projects such as:
- AI chatbots
- RAG applications
- AI agents
- LLM-powered tools
- Machine learning applications
- AI automation projects
- Cloud-based AI applications
A working project can demonstrate practical skills better than simply listing technologies on a resume.
Internship Duration & Work Model
The AI Engineering Internship is a 9-month internship program.
The role is based in Bangalore and requires interns to work from the office and collaborate closely with cross-functional teams.
Because the position involves hands-on development with domain experts, candidates should be comfortable with an in-office working environment.
Career Benefits of the AI Engineering Internship
This internship can help students gain practical exposure to:
- AI engineering
- AI agents
- LLM-based applications
- AI evaluation
- Guardrails
- Software development
- Enterprise deployment
- Cloud technologies
- Debugging
- Production engineering
For students planning a career as an AI Engineer, Machine Learning Engineer, Generative AI Engineer, or Software Engineer, this experience can be valuable.
Why Apply for This AI Engineering Internship?
The biggest advantage of this AI Engineering Internship is its practical, builder-focused nature.
Instead of only studying AI concepts, interns can work on functional prototypes, AI agents, testing systems, production-ready solutions, and enterprise deployment practices.
This can help students understand how modern AI applications are actually engineered and operated.
Final Thoughts
The AI Engineering Internship at Unisys is a promising opportunity for final-year AI/ML students who want practical exposure to modern AI engineering.
With a 9-month internship program, hands-on AI agent development, production-focused engineering, cloud exposure, and collaboration with experienced domain experts, the role can provide a strong foundation for an AI-focused career.
If you are pursuing B.Tech in Artificial Intelligence & Machine Learning, graduating in 2027/2028, and enjoy building practical AI projects, the AI Engineering Internship is worth considering.
