Senior Software Engineer – AI Applications

About the role

You will help build AI-powered software applications that support teachers’ abilities to deliver measurable results in early childhood education. You will play a pivotal role in developing intelligent systems for teachers, staff, and families with a small product development team.

Your products will both thrill and delight their users and enable our national school network to nurture young children’s originality, foster self-agency, cultivate a love for learning, and spark joy.

Requirements

• Bachelor’s degree or equivalent experience
• Eight or more years of experience developing and deploying full-stack applications, including two or more years working on AI-powered applications in production environments
• Proficiency in Python for backend development and integrating AI capabilities
• Working knowledge of TypeScript and SQL for full-stack development and data handling
• Experience integrating pre-trained foundation models, including large language models (LLMs) and multi-modal models, into production applications
• Familiarity with model evaluation techniques, such as prompt testing, output validation, and performance monitoring
• Experience with AWS services, especially those relevant to AI applications (e.g., Bedrock, Lambda, EC2, S3, RDS, DynamoDB)
• Understanding of AI safety practices, including inference validation, implementing guardrails, and handling personally identifiable information (PII) and sensitive data responsibly
• Ability to speak, read, and write English fluently

Qualifications

• Minimum qualifications

• Bachelor’s degree or equivalent experience
• Eight or more years of experience developing and deploying full-stack applications, including two or more years working on AI-powered applications in production environments
• Proficiency in Python for backend development and integrating AI capabilities
• Working knowledge of TypeScript and SQL for full-stack development and data handling
• Experience integrating pre-trained foundation models, including large language models (LLMs) and multi-modal models, into production applications
• Familiarity with model evaluation techniques, such as prompt testing, output validation, and performance monitoring
• Experience with AWS services, especially those relevant to AI applications (e.g., Bedrock, Lambda, EC2, S3, RDS, DynamoDB)
• Understanding of AI safety practices, including inference validation, implementing guardrails, and handling personally identifiable information (PII) and sensitive data responsibly
• Ability to speak, read, and write English fluently

Prior experience

• Experience with LangChain or similar frameworks for orchestrating LLM workflows and agentic behavior (e.g., tool use, planning, memory)
• Familiarity with AWS AgentCore
• Exposure to vector databases and embedding techniques, especially in retrieval-augmented generation (RAG) workflows
• Experience implementing AWS Bedrock Guardrails or similar safety mechanisms
• Understanding of LLM evaluation strategies, including prompt engineering and human feedback loops
• Experience with DevOps practices, including CI/CD pipelines, test automation, and infrastructure-as-code tools (e.g., AWS CDK)

Compensation and benefits

This is a full-time, benefits-eligible, salaried position. The full salary range for this position, across applicable United States geographies, is $157,000 - $298,000 per year. The upper portion of the salary range is typically reserved for employees who have been in the role for multiple years and have demonstrated strong performance over time. Starting salary will vary by location, qualifications, and prior experience.

This role includes 15 paid days of vacation, 4 days of paid personal time off, 9 paid days of sick (care) time, 9 paid holidays, 5 paid days off for an organization-wide winter break, and additional time off if required by applicable law. Benefits for this role include medical, dental, and vision insurance, life insurance, disability insurance, a 401(k) plan with a 4% employer contribution match, paid parental leave, an employer-matched flexible spending account for dependent care, and more. Please see here for details.

Location

Washington, Arizona, Florida, Kentucky, or Texas, within two hours’ drive to multiple Bezos Academy preschools (please see our website for-school locations); Seattle, WA preferred.

Relocation support is available for those willing to relocate to Seattle, WA

Application

Please click here for a full job description. Bezos Academy participates in E-Verify and will provide the federal government with employee Form I-9 Information to confirm authorization to work in the U.S. Bezos Academy only uses E-Verify once a candidate has accepted a job offer and completed the Form I-9. If E-Verify cannot confirm that an employee is authorized to work, Bezos Academy will give the employee written instructions and an opportunity to contact the Department of Homeland Security (DHS) or Social Security Administration (SSA) so the employee can begin to resolve the issue before any adverse employment action is taken. For more information about your right to work, please see the Notice of Right to Work. We are committed to providing reasonable accommodations to individuals with disabilities. If you are in need of an accommodation to participate in the application process, please reach out to talent@bezosacademy.org. We will work with you to ensure you have a fair opportunity to apply for our open positions. If you are a current Bezos Academy employee, please use the internal job board to apply.