Senior Software Engineer – AI Applications

As the Senior AI Applications Engineer for a new direct-to-consumer initiative at Bezos Academy, you will help build AI-powered software applications that serve educational content for children and families. A hands-on, results-driven software developer, you will play a pivotal role in developing intelligent systems for consumers with a small product development team. Your work will combine digital experiences for families with analog activities for children. With a passion for AI application development and a mission-driven mindset, you will expand access to early childhood development programs for families of all kinds.

With a proven track record of combining machine-learning models, high-quality data, and human-centered workflows into production-ready tools, you consistently deliver solutions that solve human problems. Resourceful throughout the software-development lifecycle—from research and prototyping to deployment, monitoring, and evaluation—you work effectively despite constraints on time and resources. In past roles, you’ve successfully launched AI-powered applications in collaboration with product-development teams.

As a software engineer with a customer mindset, you take pride in applying practical AI workflows and sound software-engineering principles to build impactful AI products. Adept at working from scratch, you navigate ambiguity, iterate quickly, and shape solutions that earn customer love. Hands-on experience with evaluations, inference validation, and AI guardrails has helped you strengthen the safety, performance, and ethics of AI features. You recognize exceptional work when you see it and instill that same passion in others.

In this fast-paced, start-up environment, you’ll focus on inventing, measuring, and iterating for children. Motivated equally by great products and great impact, you’re deeply inspired by our mission to expand access to quality early childhood education and experiences.

LOCATION

• Seattle, WA

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

COMPENSATION & BENEFITS

• This is a full-time, benefits-eligible, salaried position.

• The full salary range for this position in Seattle, WA is $161,000 - $255,000 per year. The upper third 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 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.

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

PREFERRED QUALIFICATIONS

• Experience with LangChain or similar frameworks for orchestrating LLM workflows and agentic behavior (e.g., tool use, planning, memory)

• Familiarity with TensorFlow or PyTorch for running inference or adapting pre-trained models

• 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)

Please click here for a full job description.

At Bezos Academy, we are committed to expanding access to play-focused preschool education in underserved communities, aiming to improve long-term educational, social, and developmental outcomes in ways that create meaningful and lasting impact.

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 [email protected]. 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.