AI Data & Infrastructure Engineer

What you'll do

• Build AI data platforms, services, APIs, and pipelines for structured, unstructured, and multimodal data.
• Implement RAG pipelines, embedding workflows, vector database integrations, and tools for observing and debugging AI systems.
• Improve platform scalability, reliability, performance, security, and cost, collaborating across engineering and product teams.

What they ask for

• Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, or a related field.
• 8+ years of experience designing and building scalable data platforms and distributed systems.
• Strong Python and SQL skills; experience with AI data pipeline orchestration, batch and streaming pipelines, cloud platforms, Kubernetes, Docker, CI/CD, and Infrastructure as Code.
• Knowledge of RAG architectures, embedding generation, vector databases, and AI data preparation for LLMs and agentic AI.

Nice to have

• Proficiency in Java or Scala.
• Experience with Generative AI, LLMs, agentic systems, API design, or manufacturing, operational, IoT, or industrial data platforms.

Pay

$184,700 to $324,800 USD base salary

Tools

Python, SQL, Java, Scala, Airflow, Kubeflow, MLflow, Spark (PySpark)

AI focus

Builds data infrastructure for enterprise GenAI and Agentic AI, including RAG pipelines, embedding workflows, vector databases, and manufacturing workflow automation.