AI Engineer — Digital Transformation

About Qube Cinema

Qube Cinema is India's leading cinema technology company, powering digital cinema distribution, content localisation, and advanced analytics across thousands of screens. Our Digital Transformation team is building the intelligence and engineering layer that drives automation, AI, and data across the business.

Role Overview

We are looking for an AI Engineer to build and deploy AI-powered solutions, data pipelines, and automation workflows at Qube Cinema. You will work on a diverse set of problems — from LLM-powered bots and NLP query interfaces to super-resolution AI models and data engineering. This is a builder role where you will ship real products that transform how Qube operates.

Key Responsibilities LLM Applications & AI Agent Development

Build and deploy LLM-powered bots, agents, and NLP query interfaces for business use cases

Integrate Claude, OpenAI, and other LLM APIs into production workflows

Design agentic workflows with tool-use, retrieval-augmented generation (RAG), and multi-step reasoning

Develop and maintain AI integrations with Microsoft Teams, CRM, ERP, and internal platforms

Data Engineering & Analytics

Build and maintain data pipelines connecting ERP, CRM, Slate, and the Qube Data Lake

Write complex SQL queries, design data models, and optimise analytical workloads

Use Python (pandas, dbt, SQLAlchemy) and R for data transformation, modelling, and visualisation

Support BI dashboard development with clean, well-structured data layers

AI & ML Model Development

Develop, train, and evaluate machine learning and deep learning models

Work on applied computer vision tasks including super-resolution (2K to 4K upscaling)

Set up GPU training pipelines, manage datasets, and track experiments (MLflow or equivalent)

Collaborate with research partners (e.g., IIT Madras) to operationalise research outputs

Automation & Integration Engineering

Build and maintain workflow automation pipelines for business process automation

Develop REST API integrations, webhooks, and event-driven pipelines between systems

Implement and manage low-code automation tools as part of broader engineering workflows

Create reusable automation scripts and CI-friendly deployment patterns

Collaboration & Documentation

Work closely with the Lead — Digital Transformation to translate business requirements into technical solutions

Document model performance, data schemas, API contracts, and deployment guides

Participate in architecture reviews and technical decision-making

Technical Skills Core (Required)

Python — pandas, NumPy, scikit-learn, FastAPI, SQLAlchemy, Jupyter

R — data wrangling, statistical modelling, ggplot2, Shiny (for dashboards)

SQL — complex queries, window functions, CTEs; experience with data warehouses (Snowflake, BigQuery, PostgreSQL)

LLM APIs — OpenAI, Anthropic Claude API; prompt engineering, function/tool calling, RAG pipelines

REST API development and consumption; JSON, OAuth, webhook patterns

Git, GitHub/GitLab — version control, code review, CI pipelines

Linux/Bash — scripting, cron, server-side automation

Deep learning frameworks — PyTorch or TensorFlow for model training

Added Advantage

Claude Code (Anthropic) — agentic coding, custom agent development, MCP integrations

Emergent AI — platform familiarity and agent deployment experience

n8n — workflow automation orchestration, custom nodes, API chaining

Computer vision — image super-resolution, ESRGAN, Real-ESRGAN, or similar architectures

MLflow, DVC, or similar — experiment tracking, model registry, reproducibility

Docker, containerisation — packaging models and services for deployment

Blockchain / Web3 basics — familiarity with Hedera or similar for IP/rights use cases

Vector databases — Pinecone, Weaviate, pgvector for embedding-based retrieval

What You Will Work On

Active projects include: an NLP sales query bot integrated with Microsoft Teams; a 2K-to-4K AI super-resolution model in collaboration with IIT Madras; P&L and revenue analytics dashboards on ERP and Data Lake; CRM data pipeline engineering across ERP, Qube Central, and Slate; and IP rights management using blockchain architecture. You will ship across all of these.

Qualifications B.Tech / M.Tech / M.Sc. in Computer Science, Data Science, Electrical Engineering, or related field

2–5 years of hands-on experience in AI engineering, data engineering, or applied ML roles

Strong portfolio or demonstrated experience building and shipping AI-powered products

Comfort working in a fast-paced, cross-functional team with shifting priorities

What We Offer Hands-on work with frontier AI tooling — LLMs, agents, computer vision, and more

Collaboration with IIT Madras on applied research projects

Direct ownership of AI products used across thousands of cinema screens

Competitive compensation, flexible working, and a builder culture