Senior AI Data Engineer: Build AI-Native Platform

Kion Group AG

Atlanta (GA)

Hybrid

USD 121,000 - 152,000

Full time

14 days+

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Benefits offered by this job

Career Development

Competitive Compensation and Benefits

Pay Transparency

Global Opportunities

Job summary

KION Group AG in Atlanta, GA, is seeking a Senior AI Data Engineer to advance our Enterprise Data Platform into an AI-native, intelligent system where AI agents can discover, understand, and interact with enterprise data and platform capabilities. This role focuses on building foundations for AI-enabled data access, governance, and scalable architectures.

You will design AI-driven capabilities, mentor engineers, and collaborate with data, AI/ML, and architecture teams to deliver high-impact

Qualifications

8-12+ years of experience in enterprise software engineering, cloud data engineering, distributed systems, or data platform development.
Hands-on experience designing and building production AI systems, AI agents, or agentic workflows integrated with enterprise applications, APIs, and platform services.
Strong understanding of AI agent architectures, including tool calling, orchestration, context management, memory, evaluation, observability, and production deployment patterns.
Experience building AI-ready data platforms with capabilities such as semantic understanding, metadata intelligence, context engineering, and trusted data access.
Strong cloud data engineering experience, preferably in GCP, including BigQuery, Pub/Sub, Dataflow/Cloud Run, Composer/ Airflow, and modern data platform services.
Strong programming skills in Python and experience building scalable software services, APIs, and microservice architectures.
Deep understanding of data engineering fundamentals, including data modeling, data contracts, metadata, lineage, governance, data quality, and batch/streaming architectures.
Experience integrating AI capabilities with enterprise data platforms and distributed systems.
Experience with modern data and cloud-native technologies such as Iceberg, Trino, Kubernetes, and Docker.
Experience designing secure, governed, and observable production AI solutions, including evaluation, monitoring, and operational excellence.

Responsibilities

Evolve the Enterprise Data Platform into an AI-native platform by enabling intelligent discovery, understanding, and utilization of enterprise data.
Design and implement AI-driven capabilities and agents that enhance data platform capabilities, automate complex workflows, and improve how data is discovered, managed, governed, and consumed.
Build the data intelligence foundation required for AI systems, including trusted context, business understanding, and reliable access to enterprise data.
Design architectures that enable AI systems to reason over enterprise data and safely interact with platform capabilities, APIs, services, and enterprise applications.
Develop scalable AI-enabled solutions that integrate with cloud data platforms, distributed systems, and modern software architectures.
Establish engineering practices for reliable production AI capabilities, including security, governance, evaluation, monitoring, and operational excellence.
Apply strong data engineering and software engineering principles to build scalable, maintainable AI-enabled platform capabilities.
Partner with data, AI/ML, architecture, and product teams to identify and deliver high-impact AI capabilities for the enterprise data platform.
Mentor engineers and define best practices for AI-enabled data platform development.