Engineering Manager, AI Feature Platform & Infra

LinkedIn; California (MO); Hybrid; USD 175,000 - 287,000; Full time

Job summary

LinkedIn is hiring to lead the Feature Platform for AI data pipelines at scale. The role blends leadership with hands-on design to process millions of QPS and multi-terabyte datasets using Spark, Beam, and Flink.

You will coach engineers, shape a long-term tech roadmap, ensure data hydration, indexing, and consistency, and collaborate across product teams to deliver high-performance feature data serving.

Qualifications

• BA/BS in Computer Science or related field; equivalent practical experience.
• 1+ year of management experience or 1+ year at staff level with management training.
• 5+ years of industry experience in software design, development, and large-scale software engineering.
• Experience programming in object-oriented languages (Java, C++, Python, Go, or Rust).
• Hands-on experience with distributed systems, databases, and large-scale data systems.

Responsibilities

• Lead, coach and manage core team of engineers building the infrastructure.
• Partner with senior management to define a long-term tech roadmap for the team and company.
• Dive deep into technical discussions to challenge status quo and steer the team forward.
• Communicate and collaborate with stakeholders across engineering and business leadership.
• Foster an inclusive environment, set clear expectations, and uphold accountability.
• Drive operational excellence, define performance metrics, and maintain a high quality bar.
• Create an autonomous, transparent, and learning-focused team culture.

Skills

Distributed systems

Data infrastructure

AI infrastructure

Education

BA/BS in Computer Science or related

MS/PhD in Computer Science or related

Tools

Hadoop

Spark

Kubernetes

gRPC

Kafka

Pinot

Flink

Venice

Job description

LinkedIn is hiring to lead the Feature Platform for AI data pipelines at scale. The role blends leadership with hands-on design to process millions of QPS and multi-terabyte datasets using Spark, Beam, and Flink.

You will coach engineers, shape a long-term tech roadmap, ensure data hydration, indexing, and consistency, and collaborate across product teams to deliver high-performance feature data serving.