AI & Full-Stack Developer - 2026 Graduates
Location: T-Hub, Gachibowli, Hyderabad (Work-from-Office)
Duration: 3 Months
Stipend: ₹15,000/month
Schedule: Monday to Saturday | 10:00 AM – 6:00 PM
Company: Altibbe Health Pvt. Ltd.
Product: HEDAMO
Apply to: [email protected]
Subject Line: Application — Graduate Full-Stack & AI Developer | 2026
Eligibility: 2026 pass-out only — degree completed and available to join immediately.
About the Role
Altibbe is hiring a 2026 graduate for a hands-on technical role at T-Hub, Gachibowli, Hyderabad.
We’re looking for someone who can use modern AI engineering tools to build, automate, test, document, deploy, and improve real software systems.
This is not a conventional internship built around observation or training exercises. The selected candidate will work on live products and internal systems from day one.
You’ll work on:
- AI agents and agentic workflows
- Workflow and task automation
- Full-stack product development
- Website testing and continuous improvement
- APIs, databases, and integrations
- Cloud infrastructure and deployment
- Terminal-based engineering and debugging
- Technical documentation and knowledge repositories
Tech Stack & Engineering Environment
Frontend: React, Next.js, TypeScript/JavaScript, Tailwind CSS
Backend & Data: Node.js, REST APIs, PostgreSQL, database design and migrations, authentication
AI & Automation: OpenAI, Anthropic or equivalent LLM APIs, prompt and context engineering, tool/function calling, structured outputs, agentic workflows, automation pipelines, retrieval and document-processing workflows
Cloud & Engineering Operations: GCP or equivalent, Linux, shell/SSH, Git/GitHub, Docker, environment variables and secrets, logs and production debugging, CI/CD fundamentals
AI Coding Tools: Claude, Claude Code, ChatGPT, Codex, Cursor, GitHub Copilot, or equivalent
Who We're Looking For
You don’t need years of professional experience.
You need evidence that you can build.
You should be able to:
- Understand an unfamiliar codebase.
- Use AI coding agents without blindly accepting their output.
- Break a problem into steps and execute it.
- Build an automation or AI workflow from scratch.
- Work confidently in a terminal.
- Connect APIs and services.
- Test your own work.
- Diagnose failures using logs and evidence.
- Write clear technical documentation.
- Identify improvements in an existing product and implement them.
- Communicate what you did, what failed, and what remains uncertain.
Personal projects, GitHub work, hackathons, deployed applications, AI experiments, automations, open-source contributions, and independently built tools are strongly valued.
Eligibility
You must be:
- A 2026 pass-out only
- Degree completed
- Available to join immediately
- Able to work from T-Hub, Gachibowli, Hyderabad
- B.Tech / BE / BSc / BCA / MCA / M.Tech or equivalent
Selection Process
The selection process begins with a practical AI engineering assignment.
Stage 1: Practical AI Engineering Assignment
Stage 2: Short Validation Call
Stage 3: In-Person Technical Assessment Day at T-Hub for shortlisted candidates
Stage 1 — Practical AI Engineering AssignmentBuild an Agentic Work Intake & Execution PrototypeObjective
Build a small but working AI application that turns unstructured incoming work — such as an email, meeting notes, founder instruction, customer request, or bug report — into a structured, reviewable, partially automated workflow.
This is a build exercise, not a design exercise.
Submit working software, not a document.
Your Prototype Must Include1. Intake
Provide a simple way to submit unstructured text.
A web interface is preferred, but a clear CLI is acceptable.
2. AI Understanding
Use an LLM to extract information using a defined structured schema, not free-form prose.
Extract:
- Task title
- Summary
- Action items
- Priority
- Detected deadline
- Missing information
- What could be automated
- What requires human confirmation
3. Agentic Planning
Generate an execution plan that routes each action as:
- Execute automatically
- Prepare for human review
- Cannot execute with available tools
- Requires clarification
Include a brief reason for each decision.
4. Real Tools / Functions
Implement at least three real tools or functions.
Examples include:
- Draft a communication
- Create a task record in persistent storage
- Generate a Markdown brief
- Run a bounded website check
- Simulate a reminder — no real calendar invites
- Search stored work
5. Human-in-the-Loop Control
At least one action must include an explicit:
Approve / Reject / Edit
step before the action is treated as complete.
Do not send real external email.
6. Persistence
Retain state between runs.
SQLite is acceptable.
Store:
- Original request
- Structured interpretation
- Action items
- Status
- Outputs
- Timestamps
7. Activity Trace
Provide a visible log showing what the system did.
The activity trace should be understandable without reading the source code.
8. Failure Handling
Demonstrate at least one sensible failure path.
The system should fail clearly rather than pretending to succeed.
AI & Agent Requirements
Use OpenAI, Anthropic, Gemini, or another accessible LLM.
Your implementation should demonstrate:
- Structured output / JSON schema
- Tool or function calling
- Multi-step execution with state passed between steps
- Validation
- Explicit agent boundaries
Frameworks such as LangChain, LangGraph, CrewAI, or similar are permitted but not required.
A simple implementation you understand is better than a complex implementation you cannot explain.
AI Coding Tools
AI coding tools are encouraged and will not be penalized.
Include a short “How I Used AI” section in your README covering:
- Tools used
- What you used them for
- One example of an AI mistake
- How you identified and fixed that mistake
Terminal & Cloud Requirements
Provide the exact terminal commands required to:
- Clone
- Install
- Configure
- Initialize
- Run
- Test
your submission.
A live deployment is strongly preferred.
Never commit API keys or credentials.
README Requirements
Your README.md must explain:
- What the application does
- Architecture — a Mermaid diagram is welcome
- Agent workflow:
- Intake → Interpretation → Planning → Tools → Approval → Persistence → Completion
- Setup instructions
- Environment variables — placeholders only
- Design decisions
- Limitations
- What you would build next — maximum 5 items
- How you used AIRequired Test Scenarios
Test your application against these three fixed scenarios and include evidence of the outputs.
Scenario 1 — Routine Business Work
Summarize a partner discussion, extract follow-ups, draft a thank-you email, and set a 7-day reminder.
Scenario 2 — Product / Website Work
Review hedamo.com, run whatever automated checks your prototype actually supports, and produce a short technical report.
Do not claim checks that your system cannot actually perform.
Scenario 3 — Ambiguous Request
Use this request:
“Please take care of the documentation and send it to everyone before the meeting.”
The system should identify and flag missing information rather than inventing recipients, documents, or meeting details.
What to Submit
Your submission must include:
- GitHub repository URL
- Live prototype URL, if deployed
- README.md
- Sample outputs from all three required test scenarios
- A screen recording of 5 minutes or less
- Resume in PDF
- GitHub profile / portfolio, if available
Your screen recording should demonstrate:
- The application
- One complete workflow
- At least one tool call
- The approval step
- The activity trace
- The project running from your terminal
Time Expectation
Approximately 3–5 hours.
A smaller prototype where every part genuinely works is better than a larger project with broken features.
AI coding tools and open-source libraries are welcome.
The work must still be something you understand and can explain, not an unchanged tutorial project.
How We'll Evaluate It
Agentic & Automation Thinking: 25%
Technical Execution: 20%
AI Engineering Judgment: 15%
Automation Quality: 15%
Terminal / Cloud / Engineering Operations: 10%
Documentation: 10%
Product Judgment & Attention to Detail: 5%
Notice what's missing: memorisation.
We care about your ability to build, reason, automate, test, debug, and explain.
A Submission May Be Rejected If
- It is a document or mockup rather than working software.
- The repository does not run using your provided instructions.
- Secrets or API keys are committed publicly.
- You cannot explain your own code.
- Outputs are fabricated or manually produced but presented as automated.
- The application silently claims success after a failure.
- The required approval step is skipped.
- There is no meaningful AI or agentic component.
- The project is substantially an unchanged tutorial.
- You are not a 2026 pass-out available to join immediately.
Code + Judgment
We’re looking for people who can combine software engineering, AI tools, automation, and sound technical judgment.
Strong candidates:
- Build rather than only discuss.
- Use AI as an engineering multiplier, not a substitute for understanding.
- Verify AI-generated code and outputs.
- Test their own assumptions.
- Diagnose problems using evidence and logs.
- Understand where automation should stop and human judgment should begin.
- Communicate limitations and uncertainty clearly.
- Care about reliability, security, and maintainability.
Ready to Build?
This role is for a 2026 graduate who wants to work directly on AI agents, automation, full-stack systems, cloud infrastructure, and production software.
Show us what you can build.
How to Apply
Email your application to:
[email protected]
Subject Line: Application — Graduate Full-Stack & AI Developer | 2026
Include:
- Resume
- Assignment repository
- Prototype URL, if deployed
- 5-minute demo video
- GitHub / portfolio, if available
- A 3–5 line introduction
Job Type: Internship
Pay: ₹15,000.00 per month
Work Location: In person
