Software Engineer III

Meta Platforms•Seattle, WA

1d•Onsite

About The Position

The Software Engineer III will support the Agentic Content Systems (ACS) organization within RL Content. The role focuses on building AI-native tooling, agentic workflows, developer surfaces, and validation infrastructure across the Frontier, Forge, and Foundations sub-teams. Work includes developing agentic workflows, engineering dashboards and other surfaces, rapidly prototyping AI-powered content tools, creating human-in-the-loop validation systems, and extending shared knowledge-layer infrastructure. The engineer will use and create AI-assisted development tools as a core part of the development workflow. The role partners with pod leads, pillar stakeholders, and cross-functional partners to define requirements, scope prototypes, and iterate on deliverables, and documents systems, APIs, and architectural decisions for post-delivery handoff.

Requirements

Bachelor's degree in computer science, software engineering, or a relevant field.
Verbal and written communication skills.
Problem-solving skills.
Customer service and interpersonal skills.
Ability to work independently and manage time.
Basic mentoring skills to provide support and constructive performance feedback.
Knowledge of the full software development lifecycle, from business and systems analysis through requirements gathering, functional specification authoring, development, testing, and delivery.
Knowledge of computer hardware and software.
Knowledge of computer development software as it relates to systems, such as SQL and VisualBasic.

Responsibilities

Design, build, and ship agentic workflows that replace manual processes.
Build and maintain tooling dashboards and surfaces that aggregate agentic signals for Content pillar leads, including new modules, pillar integrations, and UI iterations.
Explore AI-native tooling at high velocity by shipping rapid prototypes and discontinuing approaches that do not prove effective.
Discover, evaluate, and integrate new external and internal AI build tooling into Content organization development workflows.
Build validation harnesses, evaluation pipelines, and supervised-handoff ("on-the-loop") workflows for production agents.
Extend the Content Pod Manager registry and reporting infrastructure with pillar-specific customizations and leadership reporting surfaces.
Extend shared knowledge-layer capabilities by integrating new data sources and adapting to evolving search and retrieval infrastructure.
Use and create AI-assisted development tools as a core part of the development workflow to accelerate delivery.
Partner with pod leads, pillar stakeholders, and cross-functional partners to define requirements, scope prototypes, and iterate on deliverables.
Document systems, APIs, and architectural decisions for handoff after delivery.
Troubleshoot issues and make system changes as needed to resolve them.