Early Career Software Engineer – Applied AI

About Wonderschool

Wonderschool is harnessing the power of technology to provide comprehensive support to childcare providers operating out of their homes as well as in the government and non-profit sectors. Our products enable childcare providers to create high-quality environments and meet the demands of their business, while also helping parents in need of childcare solutions through the creation of an accessible marketplace.

Role Overview

We are seeking an Early Career Software Engineer with an interest in applied AI to join our growing team. This is a unique opportunity to work in a fast-paced, purpose-driven environment where you can apply your technical skills to create meaningful impact in the childcare ecosystem. You’ll collaborate with cross-functional teams to build scalable, AI-driven solutions that empower childcare providers and improve parent experiences.

Key Responsibilities

• Design, develop, and maintain robust software solutions with a focus on integrating AI capabilities.
• Collaborate with product managers, designers, and engineers to define requirements and implement innovative features.
• Design and Development of AI Agents: Build modular, task-specific AI agents capable of natural language understanding, dialogue management, and action execution using frameworks such as LangChain or Rasa.
• Debug and troubleshoot technical issues to ensure platform stability.
• Stay current with emerging technologies and best practices in software engineering and AI.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field.
• Strong foundation in programming languages (e.g., Python, JavaScript, or TypeScript).
• Familiarity with AI/ML concepts and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Basic understanding of cloud platforms like Google Cloud Platform and AWS.
• Excellent communication skills and ability to work in a collaborative, in-person environment.

Nice-to-Have Skills

• Strong understanding of machine learning principles, including model development, evaluation, and deployment for real-world applications.
• Retrieval-Augmented Generation (RAG) Pipelines: Design and deploy RAG pipelines by integrating retrievers with generative models to enable contextual, real-time responses using vectorized knowledge bases.
• Continuous Learning: Incorporate user feedback loops and data augmentation techniques to iteratively improve the performance and relevance of AI agents and RAG pipelines.

What We Offer

• Compensation: Expected salary range is $100K–$120K annually, based on experience and location.
• Health Benefits: 100% coverage for employee premiums and 80% for dependents.
• Wellness: Flexible PTO, mental wellness days, and reimbursements for wellness initiatives.
• Parental Leave: Competitive policies eligible after six months of employment.
• Work Environment: 5-6 days a week in our office in Rincon Hill, San Francisco, with lunch covered.