Website:
altibbe.com
Job details:
# 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: people@altibbe.com
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 Assignment
## Build an Agentic Work Intake & Execution Prototype
### Objective
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 Include
### 1. 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 AI
---
# Required 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:
people@altibbe.com
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
Click on Apply to know more.
