Software Engineer, Backend, Applied AI

Role overview

Responsibilities

• Identify model capability gaps and build systems, agentic pipelines, reinforcement-learning environments, and evaluations that generate training signals.
• Collaborate across product, design, operations, and infrastructure to build application experiences and implement custom user interfaces.
• Optimize code quality, efficiency, and performance; review peers' code; and work across programming languages and technologies.
• Set team direction, lead initiatives, mentor peers, and onboard team members.
• Architect scalable systems, resolve performance issues, reduce technical debt, and own components end to end.

Minimum qualifications

• Experience using data and analysis to explain technical problems and provide detailed feedback and solutions.
• Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field, or equivalent practical experience.
• Experience driving organizational change and leading complex technical projects.
• At least 8 years of programming experience in a relevant language, or at least 4 years of experience with a PhD.

Preferred qualifications

• Ongoing AI skill development and familiarity with emerging AI technologies; examples include prompt/context engineering and agent orchestration.
• Ability to solve ambiguous problems and propose process or technical improvements in a fast-moving organization.
• Experience implementing responsible AI practices such as risk assessment, bias mitigation, and quality and accuracy reviews.
• Six or more years building large-scale infrastructure applications or similar experience.
• Experience with AI training environments and quality controls, including test harnesses, automated graders, contamination detection, and taxonomy coverage.
• Experience with C, C++, or Java, and scripting languages such as Python, JavaScript, or Hack.
• Experience with code reviews, testing, rollout, monitoring, workflow improvements using AI tools, or automated synthetic-data and evaluation pipelines.

About Meta

Compensation

• Compensation depends on skills, qualifications, experience, and location; the posting does not specify a particular pay amount or cadence.
• Base compensation may be supplemented by benefits and, where applicable, bonus, equity, or sales incentives.