Senior Data Engineer

Overview

Help build the world's most advanced brand-consistent AI content generation platform at Inku.

We are on a mission to create the most sophisticated brand identity AI system in the world. This system will ingest and understand every facet of a brand—from visual guidelines and product imagery to company culture and video content—to generate content that feels unconsciously on-brand. Our platform will power the creation of production-ready 4K assets that seamlessly blend brand authenticity with AI-generated creativity.

The Data team at Inku is responsible for all aspects of data preparation and brand identity modeling that powers our generation workflows. We build the data foundation layer that connects brand materials to AI outputs, ensuring every generated image achieves 100% on-brand accuracy across all criteria. We're an interdisciplinary team working across the full stack—from ingestion pipelines to model training to production deployment—learning from each other and collaborating to create a platform that feels magical to use.

We work in 2-3 week cycles with rotating project ownership in a flat organisational structure. You'll be working directly with our CTO and a team of engineers with strong software and AI backgrounds, with significant autonomy to shape both technical architecture and product direction.

We are looking for an outstanding individual excited about joining us to lay the groundwork for our production platform. In particular, we are looking for a candidate who:

• Is passionate about the intersection of brand identity, creative workflows, and AI systems
• Will thrive in a startup environment where you'll wear multiple hats and move fast
• Has deep expertise in data engineering and pays close attention to the details that make AI outputs feel authentic
• Demonstrates a proactive attitude and enthusiasm for exploring new approaches to brand representation
• Can effectively balance multiple responsibilities as we build towards production

Responsibilities

• Design and build robust data pipelines that ingest and process diverse brand materials (images, videos, style guides, company documents, existing creative assets)
• Create the data foundation layer that enables our AI to understand and maintain brand consistency across all generated content
• Build and optimize graph database architectures to model complex relationships between brand elements, visual styles, and creative attributes
• Build infrastructure to store, version, and efficiently retrieve the multimodal data needed to power our generation models
• Partner with AI engineers to improve on-brand accuracy through careful experimentation and data-driven iteration
• Develop systems to measure and track brand consistency metrics, moving us from current 50% (2/4 criteria) to 100% (4/4 criteria) accuracy
• Collaborate across our small team to identify gaps in model performance and translate them into data improvements
• Helps establish engineering practices and technical foundations as we scale to production

Qualifications

Required:

• 4+ years of experience in data engineering, building production data pipelines and infrastructure
• Strong programming skills (Python required; experience with data processing frameworks)
• Experience working with large-scale data storage and retrieval systems
• Experience with cloud infrastructure (GCP strongly preferred)
• Proven ability to work independently and take ownership of complex technical challenges
• Comfort with ambiguity and excitement about defining systems from the ground up
• Experience with graph databases (Neo4j, TigerGraph, or similar) and knowledge graph construction
• Proven experience building scalable ETL pipelines for large-scale data processing
• Strong PostgreSQL experience, including schema design, query optimization, and performance tuning

Preferred:

• 6+ years of experience in data engineering or related fields
• Strong GCP expertise, particularly with GPU compute, scaling strategies, and cost optimisation
• Experience with multimodal data (images, video, text) and computer vision pipelines
• Familiarity with AI/ML workflows and model training infrastructure
• Background working in creative industries or with brand identity systems
• Experience at early-stage startups or building 0→1 products
• Knowledge of GPU compute infrastructure and optimisation for inference workloads