Team
Planhat is a global leader in Customer Management solutions and we’ve been building toward our AI Platform (AIP) for some time and now.
As part of this journey, we’ve recently launched a new initiative to guarantee its efficacy: the AI Deployment Program (ADP)—a dedicated services team with deep expertise in deploying CX-enhancing AI capabilities, powered by the Planhat platform.
Mission
AI is only as powerful as the data it’s trained on. At Planhat, our platform powers some of the most valuable customer data in the world—but unlocking its full potential requires strong engineering.
We’re looking for Forward Deployed AI-focused Data Engineers to design, build, and optimize the data pipelines that power our AI Workflows, AI Automations, and customer operations.
This isn’t a backroom ETL role—you’ll work directly with our Forward Deployed Solutions team and strategic customers to transform messy, complex datasets into clean, structured, and reliable fuel for AI models.
You’ll own the process from end to end: embedding with customers to understand their systems, engineering pipelines that deliver at scale, and working closely with our commercial teams to build workflows and solutions that our customers are asking for.
Role
Architect and implement high-performance data pipelines for AI applications.
Design and optimize and transform raw customer data into structured, reliable datasets.
Build AI workflows and data mapping in the Planhat platform
Work with SQL, Python, and APIs to integrate multiple, messy, distributed systems.
Partner with AI engineers to ensure models have the clean, context-rich data they need.
Build monitoring and validation systems to ensure data quality and trust.
Collaborate with customers and internal teams to solve complex, domain-specific data challenges.
Skillset
5+ years experience in data engineering, ideally in B2B or AI-focused environments.
Strong expertise in SQL, data modeling, and ETL/ELT tools.
Proficiency with Python or similar scripting languages.
Experience integrating with REST/GraphQL APIs and building data ingestion frameworks.
Understanding of data quality, governance, and observability best practices.
Experience with ML pipelines, vector databases, or RAG architectures.
Willingness to travel to customer sites as needed.
Advantages
You’ll:
work at the intersection of AI, customer data, and real-world outcomes.
get to solve complex data problems for some of the world’s most innovative companies.
be part of a small, high-caliber team with the autonomy to design and own your work end-to-end.
