Senior Software Engineer

MA Boston
33 Arch Street
Boston, MA 02110, USA

Britebound is a national nonprofit that is changing the way kids learn about careers and prepare for their futures through access to career‑readiness information and experiences.

Britebound fulfills its mission through free digital‑first direct experiences, philanthropy, advocacy, thought leadership, groundbreaking research, and impact investing. We believe that exploring career possibilities, as early as middle school, and providing access to education‑to‑career pathways aligned with one’s passions and goals will result in greater confidence and long‑term success for all students.

We are seeking an AI‑experienced Senior Software Engineer to contribute to the design, development, and maintenance of AI‑driven applications to augment internal processes. These augmented internal processes will accelerate and improve criteria operations through Britebound. The engineer also will contribute features to Britebound’s direct‑to‑consumer web platforms. In this role, you will focus on building scalable, secure, and user‑friendly applications, data transformation, and systems integrations.

You will work closely with product managers, designers, engineers, and data analysts to apply your software engineering skills and AI‑domain experience across the full technology stack to deliver impactful digital solutions.

This role is ideal for someone who enjoys hands‑on coding, problem‑solving, and collaborating in a cross‑functional environment while continuing to grow their technical expertise on a tightly integrated team of technologists.

• Core Engineering
  • Develop, test, and maintain cloud applications using modern frontend (React, Type Script) frameworks
  • Design and implement AI‑driven solutions deployed as cloud applications or services using Python or Azure frameworks and platforms.
  • Design and articulate technical solutions that deliver cross‑cutting value across business goals.
  • Contribute to the design and implementation of databases (SQL, No
    
    SQL) in Snowflake data warehouses and cloud‑based solutions (AWS, Azure, or equivalent).
• AI & LLM‑Focused Responsibilities
  • Design, build, and deploy LLM‑powered features, including chatbots, AI agents and AI assistants that support learners and internal teams
  • Integrate and orchestrate LLM APIs from providers such as OpenAI, Anthropic, and Google Gemini, selecting models and approaches appropriate to cost, latency, and accuracy requirements.
  • Implement retrieval‑augmented generation (RAG) pipelines using vector databases and embeddings to ground LLM responses in trusted, domain‑specific content.
  • Develop prompting strategies, system prompts, and evaluation techniques to improve response quality, safety, and reliability.
  • Collaborate with product, design, and data teams to define human‑centered conversational UX patterns and guardrails appropriate for educational contexts.
  • Monitor, test, and iterate on LLM applications using logging, analytics, and automated evaluation frameworks.
  • Address privacy, security, bias, and content safety considerations when deploying AI‑driven features, especially in environments involving minors or sensitive educational data.
• Review and guide the work of other engineers, ensuring adherence to best practices, maintainability, and performance standards.
• Act as a technical mentor—supporting the growth and effectiveness of mid‑level and junior engineers.
• Stay up‑to‑date with emerging AI technologies and propose pragmatic, mission‑aligned applications.

• Technical Requirements
  • Core Engineering
    • 6+ years of professional experience in full‑stack software development.
    • Demonstrated expertise with modern frontend frameworks (React, Material UI, or similar) and backend development (Node.js, Express, APIs).
    • Strong understanding of software architecture, system design, and cloud infrastructure.
    • Proficiency with CI/CD, containerization (Docker, Kubernetes), and version control (Git).
    • Experience working with cloud services such as AWS, Azure, or Firebase. (Preference to Azure)
  • AI & LLM Experience
    • Hands‑on experience building production LLM‑based applications, such as chatbots, assistants, or AI‑enhanced workflows.
    • Familiarity…