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🌐 Remote💼 Full-time🗓 2026-06-25

Core

Designing and optimizing scalable backend systems, APIs, and data pipelines for an AI-powered bias detection and compliance platform.

Role type

Backend Engineer Intern

Builds

Scalable backend services, data pipelines, and API integrations for bias detection tools.

Domain

AI governance, algorithmic fairness, and regulatory compliance.

Deliverable

production ML models

Required skills

Backend programming (Python, Node.js, Go), Database management (SQL/NoSQL), Cloud services (AWS, GCP, Azure), Containerization (Docker, Kubernetes), API design, Microservices architecture.

Preferred skills

Ethical AI knowledge, Data privacy law familiarity, Security practices, Compliance platform experience.

Technologies

Python, Node.js, Go, SQL, NoSQL, AWS, GCP, Azure, Docker, Kubernetes.

Responsibilities

Design and implement APIs and microservices for compliance tools; Integrate AI models into production environments; Develop data pipelines for bias analysis and risk scoring; Ensure system scalability and regulatory compliance; Collaborate with frontend teams on service integration.

Seniority

Intern

Rewrite
## About the Role We're seeking a Backend Engineer Intern Fellow passionate about building scalable, ethical, and resilient systems. You'll contribute to the architecture that powers FairwAI's bias detection and compliance platform, ensuring robust data processing, security, and compliance readiness. This role is ideal for students or early-career professionals with an interest in AI systems, backend engineering, and responsible technology deployment. ## Key Responsibilities - Design, implement, and optimize APIs and microservices supporting compliance and bias detection tools. - Work with leadership and research teams to integrate AI models into production environments. - Ensure system scalability, reliability, and compliance with global data protection regulations. - Develop data pipelines for bias analysis, risk scoring, and compliance reporting. - Collaborate with frontend engineers to ensure seamless integration of backend services. ## Preferred Qualifications - Strong foundation in backend programming (Python, Node.js, or Go). - Familiarity with databases (SQL/NoSQL), cloud services (AWS, GCP, or Azure), and containerization (Docker, Kubernetes). - Interest in ethical AI, compliance frameworks, or data governance. - Self-starter with the ability to work in a fast-paced, remote-first team. - Bonus: Knowledge of security practices, data privacy laws, or prior work with compliance platforms. ## What You'll Gain - Hands-on experience in deploying backend systems that support ethical AI. - Exposure to international compliance standards and AI governance practices. - Mentorship from engineers and advisors from MIT, Harvard, and UN-affiliated organizations. - Opportunity to build portfolio-ready backend solutions with social impact. - Flexible work schedule + fully remote culture. This role is unpaid. - Top-performing fellows may be referred to graduate fellowships, future paid roles at FairwAI, or supported in publishing technical findings. ## About the Company FairwAI is an AI-powered bias detection and compliance platform transforming how industries address algorithmic discrimination. We're building the regulatory infrastructure of the future—starting with hospitality, and expanding into healthcare. Our mission: to ensure that AI works fairly for everyone. Our team includes collaborators from MIT, Harvard, Stanford, and global institutions tackling digital rights, inclusive capitalism, and tech ethics. This internship is offered through our 501(c)(3) nonprofit organization, which focuses on education, healthcare, and economic development. As a nonprofit, we are able to host unpaid interns in compliance with U.S. labor law and CPT/OPT eligibility guidelines. International students with CPT or OPT authorization are welcome. ## About the Role (Shaurjya Mandal – Head of Research, AI Systems & Clinical Innovation) Role: Shaurjya leads FairwAI's research function and the development of its AI methodology — including structured retrieval architectures, sentiment and bias detection systems, and validation frameworks for fairness in clinical and high-stakes AI environments. He ensures FairwAI's research meets the standards of peer-reviewed clinical AI while remaining accessible and useful in real-world deployment. Bio: Shaurjya Mandal is a machine learning research scientist at Mass General Brigham and Harvard Medical School, where he develops and evaluates AI systems for clinical settings. His research sits at the intersection of responsible AI, healthcare equity, and applied machine learning — with published and applied work in algorithmic bias, fairness in clinical decision support, and AI safety for vulnerable populations. He holds an M.S. in Artificial Intelligence from Carnegie Mellon University, where he conducted research at the Robotics Institute on machine perception and learning systems. Prior to his work at Harvard, Shaurjya served as a research engineer at India's Defence Research and Development Organisation (DRDO) and contributed to AI policy and infrastructure projects across the MENA region, including the design of responsible AI deployment frameworks for healthcare and insurance systems in the United Arab Emirates. He is a Nucleate Pittsburgh fellow, a recognized convener in early-stage biotechnology and AI commercialization. At FairwAI, Shaurjya bridges frontier clinical AI research with practical, ethical deployment — ensuring that what we build for the most underserved populations is also held to the highest scientific standard.
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