Agentic Engineer for AI Video Creation

TrueFan AI

Gurugram, Haryana, India

Company: TrueFan AI

Location: Gurgaon, India (On-site)

Function: AI / Generative AI Engineering

About TrueFan AI

TrueFan AI is a generative-AI platform building AI-powered celebrity video ads and

hyper-personalized marketing solutions for Indian brands. We work at the intersection of

GenAI, video, voice, and automation , building production systems that create content at

scale.

About the Role

We are looking for an AI Engineer experienced in building large-scale, agent-driven

video generation pipelines .

You will build systems where AI agents orchestrate multiple models and tools to take a video

brief from idea → script → scenes → generation → voice/lip-sync → editing → validation → final video .

This role sits at the intersection of AI agents, generative video, backend engineering, and

distributed systems . The ideal candidate is a hands-on builder who can take experimental

AI capabilities and turn them into reliable, scalable production systems.

What You'll Do

Agentic Video Generation

Build multi-step AI agents that autonomously plan and execute video-generation workflows.
Orchestrate LLMs, image/video generation models, TTS, voice, lip-sync, avatars, and other AI tools.
Design agent state, tool calling, planning, validation, retries, fallbacks, and human-in-the-loop workflows.
Build systems that can dynamically decide the next step based on intermediate outputs.

Scale & Infrastructure

Build high-throughput video-generation pipelines capable of processing large batches and concurrent jobs.
Design asynchronous workflows using queues, workers, APIs, and distributed systems.
Optimize pipelines for quality, latency, throughput, reliability, and cost .●
Build robust handling for failures, retries, timeouts, partial outputs, and long-running
jobs.

AI & Video Engineering

Integrate and evaluate new generative video, image, audio, and multimodal models.
Build automated video-processing workflows using tools such as FFmpeg .
Develop pipelines for compositing, rendering, subtitles, audio/video synchronization, and asset management.
Build evaluation and quality-control systems for generated content.

Production Engineering

Build production-grade Python services and APIs.
Implement monitoring, logging, tracing, error handling, and automated validation.
Debug issues across the entire AI pipeline, from agent decisions to model failures and rendering jobs.
Take systems from prototype → production → scale.

What We're Looking For

2–4 years of experience in AI/ML, software engineering, or generative AI.
Hands-on experience building video-generation or generative-media pipelines .
Strong Python and backend engineering fundamentals.
Experience building LLM-powered agents and multi-step workflows.
Experience integrating multiple AI models/APIs into production pipelines.
Strong understanding of asynchronous processing, queues, workers, and distributed systems.
Ability to build reliable systems at scale with a focus on latency, cost, and throughput.
Strong debugging, problem-solving, and ownership mindset.

Nice to Have

Experience with LangGraph, LangChain, CrewAI, or similar agent frameworks .
Experience with video-generation models, TTS, voice cloning, lip-sync, avatars, or multimodal AI.
Experience with FFmpeg, GPU inference, or distributed GPU workloads .
Experience with Celery, RabbitMQ, Redis, Kafka, Docker, or cloud infrastructure.
Experience building evaluation systems for generative AI.

Our Stack

AI / Agents: LLM APIs, Agent Frameworks, Multimodal AI

Generative Media: Video, Image, Voice, TTS, Lip-sync

Backend: Python, FastAPI

Video Processing: FFmpeg

Orchestration: Celery, RabbitMQ, Redis, Background WorkersInfrastructure: Docker, Cloud / GPU Workloads

Database: MySQL / PostgreSQL

What Success Looks Like

Build and ship agentic video-generation pipelines at scale .
Automate the journey from a video brief to a finished video with minimal manual intervention.
Reliably orchestrate multiple AI models and tools.
Improve video quality, pipeline speed, reliability, and cost.
Build infrastructure capable of handling large volumes of concurrent video-generation jobs.
Rapidly integrate and productionize new AI models and capabilities.

This is a builder's role for someone excited about making AI agents capable of creating complete videos — autonomously and at scale.