Internal Platforms & SRE Engineer — Scale & Reliability

Neura Market; San Francisco (CA); Hybrid; USD 180,000 - 260,000; Full time

Benefits offered by this job

Health, dental, and vision coverage

Wellness stipend

Commuter stipend

401k plan with company match (USA)

Flexible paid time off

Job summary

Lambda is seeking a skilled professional to join the Information Systems group in San Francisco or San Jose. You will design and improve internal IT systems and platforms, with a focus on reliability and automation.

The role involves collaboration across Engineering, Finance, GTM, and People to scale tools, automate workflows, and ensure secure data flows. The position emphasizes designing for performance and scalability across multiple clouds (AWS, GCP, Azure), and requires hands-on scripting

Qualifications

• Experience designing and operating large-scale distributed systems.
• Proficiency in Python and Go or similar languages.
• Strong cloud platform experience across AWS, GCP, and Azure.

Responsibilities

• Design, write, and deliver software and services to improve internal IT systems and platforms.
• Automate response to non-exceptional events and prevent recurrence.
• Collaborate with Engineering and internal teams to define designs, architectures, standards for large-scale systems.
• Engage in capacity planning, performance analysis, and system tuning.
• Produce documentation and artifacts for the systems you are responsible for.

Skills

AWS

GCP

Azure

Python

Go

Terraform

Chef/Ansible

GitHub Actions

System design

Tools

Chef

Ansible

Terraform

GitHub Actions

Job description

Lambda is seeking a skilled professional to join the Information Systems group in San Francisco or San Jose. You will design and improve internal IT systems and platforms, with a focus on reliability and automation.

The role involves collaboration across Engineering, Finance, GTM, and People to scale tools, automate workflows, and ensure secure data flows. The position emphasizes designing for performance and scalability across multiple clouds (AWS, GCP, Azure), and requires hands-on scripting