Full Stack AI Engineer(Vibe coding)

About Us

Screen Andragogy Platforms is a technology management solutions company for the screen industries. We empower industry professionals, organizations, and educational institutions with tools and data-driven insights. Committed to innovation, we leverage advanced analytics to uncover actionable intelligence that drives success across every stage of the creative process. From analyzing market trends and audience preferences to optimizing production and distribution strategies, our research provides unparalleled depth to inform strategic decision-making.

Job Overview

Role: Full Stack AI Engineer (Vibe Coding Focus)

We are seeking a proactive, product-minded Full Stack AI Product Engineer to join our team. This role sits at the intersection of AI product strategy, vibe coding, growth experimentation, AI agents, and full-stack execution.

You will help conceptualize, prototype, test, and scale AI-powered products for the media and entertainment ecosystem. This is not a conventional engineering role it is a builder role with strong product intuition, rapid execution, and ownership over AI-driven workflows. Successful completion may lead to a permanent role.

Key Responsibilities

AI Product & Strategy

• Translate business and industry problems into AI-powered product features and workflows.
• Define AI use cases, product scope, MVPs, and iteration roadmaps.
• Collaborate with founders and stakeholders on AI product vision, positioning, and growth strategy.

Vibe Coding & Rapid Prototyping

• Practice vibe coding: rapid iteration, experimentation, and shipping usable prototypes fast.
• Build proof-of-concepts using modern AI stacks rather than overengineering early solutions.
• Balance speed, functionality, and user experience while validating product-market fit.

Full Stack Development

• Build end-to-end applications:
• Frontend: React, Tailwind CSS, HTML/CSS
• Backend: Node.js, Python, APIs, databases
• Integrate AI agents and automation workflows into core product features.

AI Agents & Prompt Engineering

• Design, build, and optimize AI agents for research, content, analytics, and automation.
• Develop and maintain prompt libraries, smart prompts, and agent logic.
• Implement workflows using LLMs, retrieval systems, and orchestration frameworks.
• Continuously improve prompts for accuracy, efficiency, and user outcomes.

AI Integration

• Integrate NLP, ML models, and LLM APIs (OpenAI, Hugging Face, etc.).
• Assist in deploying AI features such as:
• AI assistants
• Smart recommendations
• Automated analysis and insights
• Work closely with data and AI specialists to ensure scalability and reliability.

Growth & Experimentation

• Support growth strategies through feature experimentation and user feedback loops.
• Analyze usage patterns to optimize onboarding, engagement, and retention.
• Assist in A/B testing, feature validation, and iteration cycles.

UX/UI & Product Experience

• Collaborate on user journeys, wireframes, and interaction design.
• Ensure AI features feel intuitive, explainable, and valuable.
• Balance aesthetics with functional product thinking.

Testing, QA & Performance

• Write automated tests (unit, integration, end-to-end).
• Ensure quality, reliability, and performance of AI-powered systems.
• Debug, optimize, and scale applications efficiently.

Media & Entertainment Domain Application

• Apply knowledge of the screen industries to product design and AI use cases.

What You’ll Learn

• AI-first product thinking and AI Product Management.
• Building and scaling AI agents and prompt-driven systems.
• Rapid prototyping through vibe coding methodologies.
• Growth-oriented product development and experimentation.
• Full-stack AI systems used in real-world media and entertainment workflows.
• Industry-grade testing, QA, and deployment practices.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Design, or equivalent experience.
• Strong fundamentals in front-end development (React, JS, Tailwind, HTML/CSS).
• Proficiency in Node.js and Python, especially for AI-driven workflows.
• Interest in AI products, LLMs, prompt engineering, and AI agents.
• Product-oriented mindset with strong problem-solving skills.
• Familiarity with UX/UI design principles and tools (Figma, Sketch, Adobe XD).
• Curiosity about the media & entertainment industry and its evolving tech stack.
• Comfort with fast iteration, experimentation, and ambiguity.

Bonus Skills (Highly Valued)

• AI tools: OpenAI APIs, Hugging Face, LangChain, AutoGen, CrewAI, or similar agent frameworks.
• Experience with prompt engineering, RAG pipelines, or AI orchestration.
• Growth experimentation, metrics, and analytics experience.
• Automated testing tools (Jest, Cypress, Pytest).
• Cloud platforms (AWS, GCP) and CI/CD pipelines.
• Prior experience as:
• AI Product Manager
• Full Stack AI Engineer
• AI Prototyper
• zero-to-one product builder

Application Process

Creative Product Test

Objective:

Build a small AI-powered product or feature that solves a real problem in the media or entertainment ecosystem. Strong emphasis on:

• Product thinking
• UX/UI
• AI agents or prompt-based workflows

Timeframe: 2 hours

Evaluation Criteria:

Product intuition, originality, AI usage, UX, clarity, and execution.

Technical + Product Thinking Test+behavioural Round

• Short challenges assessing:
• Full-stack implementation
• Python & AI integration
• Prompt engineering & agent logic
• AI Analytics
• Growth Strategies

Timeframe: 2 hours

Mandatory Policy

🛑 No direct full-time employment is offered at the outset.

✅ All selected candidates must first complete a minimum 3-6 months internship or consulting engagement.

🌍 Willingness to travel with the company for at least 1–2 years is mandatory. This ensures:

• Cultural alignment across global markets
• Real-time collaboration with clients and project stakeholders

Post successful completion of this phase, candidates may be considered for full-time roles, based strictly on:Value creation ,Strategic alignment,Contribution to the Screen Andragogy Platforms ecosystem

Important Note: Internship vs Project-Based Consulting Engagement

We follow a strict engagement structure based on the academic stage of the applicant to ensure seriousness, fairness, and real industry alignment.

Internship Eligibility (Undergraduate Only – Early Years)

Traditional internships are offered only to undergraduate students in:

• 1st year
• 2nd year
• 3rd year

These internships are designed for:

• Early exposure to AI, product development, and industry workflows
• Learning-focused participation under supervision
• Limited responsibility and structured guidance

Early-year internships are NOT intended for:

• Ownership of core product features
• Client-facing or production-grade deliverables
• Long-term employment evaluation

They exist purely for foundational learning and orientation.

Final-Year Undergraduate & Postgraduate Policy

For the following candidates:

• Final-year undergraduate students (4th year or equivalent)
• Postgraduate students (any year)
• Recent graduates

👉 Traditional internships are NOT offered

Project-Based Consulting Engagement (Mandatory for Final-Year & Above)

Eligible candidates from the above categories will be onboarded through a Project-Based Consulting Engagement instead of an internship.

Nature of the Engagement

• You will join as a Project Consultant, not an intern
• You will work on live AI products, platforms, and internal systems
• You will be assigned clearly defined deliverables, milestones, and timelines
• Output is expected to be production-quality, not academic or experimental
• The role mirrors AI product team standards, including ownership and accountability

This model is rigorous, execution-driven, and performance-evaluated.

Why We Do Not Offer Internships at This Level

Final-year undergraduate and postgraduate candidates are expected to:

• Demonstrate professional-level capability
• Work independently with minimal supervision
• Contribute meaningful value to core products and AI workflows
• Be evaluated as potential full-time hires, not trainees

Traditional internships do not meet these expectations and therefore are not suitable for this level.

Evaluation & Outcomes

All project-based consultants are evaluated continuously on:

• AI product thinking and execution
• Full-stack and AI agent implementation
• Prompt engineering and workflow design
• UX/UI sensibility
• Speed, quality, and reliability of delivery

Based on performance:

• Top performers may be offered permanent full-time roles
• Others exit with verifiable, real-world project credentials
• Performance-based references are provided where applicable

How to Apply

Submit your Video resume, portfolio, GitHub, and AI/LLM projects via LinkedIn.

We’re looking for builders who can think in products, ship fast, and harness AI creatively to shape the future of the screen industries