Senior AI Engineer – Customer & Marketing SystemsVerified as a real position

Who we’re looking for

• Significant hands-on experience architecting, deploying, and maintaining production-grade AI/ML systems at scale.
• Deep expertise within the GCP ecosystem , especially with BigQuery and Vertex AI, alongside hands-on vector database utilization.
• Strong data modeling skills (relational and dimensional) with experience handling high-volume customer datasets and event schemas.
• Advanced Python proficiency and deep familiarity with machine learning frameworks, LLMs, and RAG architectures.
• Familiarity with marketing tech infrastructure —such as CRMs, CDPs, or automation tools—and a solid grasp of data privacy (e.g., GDPR).
• A strong bias for action and automation , thriving in a lean, fast-paced environment where we value speed over perfection and iterate in real-time.
• Strong written and verbal communication skills in English language , with the ability to articulate complex technical decisions to diverse stakeholders.

What you’ll do

• Design and deploy scalable AI/ML systems that power our customer platforms, focusing on personalization, semantic search, and retrieval-augmented generation (RAG).
• Own our vector database strategy using technologies like Vertex AI Vector Search, pgvector, or Pinecone to support high-scale similarity search.
• Define and govern key data models in BigQuery, capturing complex customer behaviors, campaign interactions, and event schemas.
• Build robust retrieval and embedding pipelines to integrate AI-driven intelligence into our CRM, CDP, and marketing automation tools.
• Architect and launch AI services on GCP utilizing Vertex AI, Cloud Run, GKE, Dataflow, and Pub/Sub.
• Partner directly with product and marketing teams to turn customer and commercial opportunities into highly optimized AI/ML products.
• Set engineering standards for AI production reliability, leading system evaluations, and guiding fellow engineers through technical design and code reviews.

About the position

Kiwi.com is a leading global travel-tech company headquartered in the Czech Republic. Our innovative algorithm enables users to find better route options and prices other search engines can’t see, daily performing billions of price checks across 95% of global flight content. Are you bold, bright and curious? Join a global business that’s still got a start-up heart. About our Customer & Marketing Engineering Team In the Kiwi.com Customer & Marketing Engineering team, we focus on building intelligent systems that drive how we interact with millions of global travelers. Working with a Google Cloud-native stack, our mission is to leverage cutting-edge AI, machine learning, and semantic search to personalize travel discovery and campaign automation. We build for depth and speed, deploying models that have an immediate business impact and directly shape the customer journey.

Benefits

• Your hands-on experience and drive to inherently use AI (Cursor or Claude Code) to eliminate manual development steps and accelerate your daily impact.
• Your strong analytical mindset and ability to evaluate multiple technical paths, navigate complex payment processes, and mitigate potential security risks.
• You are fluent in English with excellent written and verbal communication skills, ensuring clear and empathetic collaboration within lean, high-talent teams.
• You have a proven track record of debugging complex issues and driving long-term, sustainable technical fixes.
• You are fluent in Python and enjoy working with clean, stable, and maintainable code bases.
• Hands-on experience with relational databases—mainly PostgreSQL and Redis—along with a data-driven familiarity with BigQuery.
• Your solid knowledge of object-oriented design patterns, microservices architecture, REST principles, and asynchronous messaging systems like PubSub.
• You have a proven track record of sharing responsibility for deployment flows, showing a commitment to team success by collaborating on how we safely manage, nurture, and maintain our cloud infrastructure.