Embedded Software Engineer Relocation Jobs in Miami, FL

As a Senior AI Applications Engineer at Bezos Academy, you will help build AI-powered software applications that support teachers' abilities to deliver measurable results in early childhood education. As a hands-on, results-driven software developer, 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.

You have 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 have 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 high-impact 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 role, you will focus on building, measuring, and iterating for children. Motivated equally by great products and great impact, you are deeply inspired by our mission to expand access to quality early childhood education and experiences.

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.

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.

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 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).