Software Engineer, Content Safety, AI Transformation Enablement

• Build high-quality systems that help your team deliver on its commitments to clients, ensuring effective and performant solutions to content safety problems.
• Own the design and implementation of robust, modular software components to ensure clean, readable, and maintainable code.
• Implement and maintain both stateless and stateful agentic flows, supporting multi-step AI orchestration pipelines that interact securely with Application Programming Interfaces (APIs), databases, and external tools.
• Develop and test validation gates, routing logic, and tool-use schemas to guarantee deterministic and compliant execution within our autonomous safety agent pipelines.
• Build and deploy production-grade content safety solutions across both server-side and on-device environments.

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
• 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• 1 year of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), or specialization in another ML field.

Preferred qualifications:

• Experience integrating Generative AI APIs, foundation model Software Development Kits (SDKs), and calling cloud-hosted models within software applications.
• Experience designing clean software components, modular interfaces, and robust data models within complex systems.
• Experience implementing or testing agentic flows (e.g., both stateless and stateful) and multi-step AI orchestration pipelines, including prompt engineering and tool-use (e.g., function calling) schemas.
• Basic understanding of ML concepts and how Large Language Models (LLMs) work (e.g., high-level mechanics of transformers, embeddings, or model activations).
• Familiarity with or interest in Responsible AI or safety-adjacent fields such as factuality, policy enforcement, or adversarial defense.

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
• 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• 1 year of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), or specialization in another ML field.