Full-Time Staff Software Engineer, Data & AI

We are seeking a Staff Software Engineer with a platform mindset to help shape the future of our enterprise-wide Data, Analytics, and AI/ML platform capabilities.

This role focuses on building foundational platform capabilities, not individual models.

Responsibilities:

• Architect and build core platform components for the data, analytics, and AI/ML lifecycle (data processing, feature engineering, model training/serving, observability, governance).
• Define solution architectures for internal platform capabilities and common AI/analytics use cases.
• Lead build vs. buy evaluations for MLOps frameworks, vector stores, orchestration layers, and AI development tools.
• Stay current with modern data and ML architectures (lakehouses, LLM orchestration, multi-tenant model serving).
• Partner with engineering, data science, and product teams to enable enterprise-scale platform service adoption.
• Guide platform integration with cloud services (AWS), CI/CD pipelines, and observability stacks.
• Drive internal adoption across global and regional product lines.
• Mentor engineers on platform best practices, architecture, and scalability.

Requirements:

• 8+ years of software engineering experience, specializing in building platforms for data, analytics, or AI/ML workloads.
• Strong background in distributed systems, cloud-native architecture, and data-intensive platforms.
• Proficiency in Python, Java, or Scala.
• Experience with big data processing frameworks (Spark, Flink) and modern data architectures (Lakehouse, Delta Lake, Apache Iceberg).
• Experience with cloud platforms (AWS), Infrastructure-as-Code tools (Terraform, Helm), Docker, Kubernetes, and production CI/CD pipelines.
• Track record of architectural leadership, influencing technology adoption, and driving platform reuse.

Preferences:

• Experience building internal ML platforms, MLOps frameworks, or self-service data science environments.
• Exposure to LLM-based applications, GenAI tooling (LangChain, vector databases, prompt orchestration).
• Understanding of security, compliance, and governance requirements for AI/ML workloads.
• Familiarity with platform observability (logs, metrics, tracing).

What is the last date for applying to the job?

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