Software Engineer I to build and scale AiPrise’s compliance platform, working across backend APIs, microservices, data pipelines, integrations, and customer-facing tools.
Company Details
AiPrise is an AI-powered global compliance platform helping fintechs, marketplaces, and payment companies with KYC, KYB, AML, fraud prevention, and risk management. AiPrise
Requirements
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2 years of professional software engineering experience.
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Strong programming fundamentals in Python, Go, Java, Node.js, or a similar backend language.
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Experience building REST APIs, microservices, or distributed systems.
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Strong understanding of relational databases such as PostgreSQL or MySQL.
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Familiarity with Git, CI/CD, Docker, and modern deployment practices.
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Strong debugging and problem-solving skills.
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Good communication and ability to translate business requirements into technical solutions.
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Experience with fintech, payments, fraud, compliance, AI/ML, event-driven systems, React/TypeScript, NoSQL, or infrastructure-as-code is a plus.
Responsibilities
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Design, develop, and ship production features across backend APIs, data pipelines, integrations, and case management tools.
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Own features end-to-end from requirements and implementation through deployment and monitoring.
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Build scalable REST APIs and microservices integrating with compliance vendors.
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Develop KYB/AML case management workflows and business logic.
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Build data pipelines for ingesting, transforming, and routing compliance data.
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Integrate third-party identity and compliance APIs.
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Write clean, maintainable, tested, and documented code.
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Participate in code reviews and engineering best practices.
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Debug production issues and improve system reliability, performance, and cost efficiency.
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Build monitoring, alerting, and observability into production features.
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Collaborate with product, compliance, and customer success teams.
Job Details
HSR, Bengaluru, Karnataka, India
Interview Process
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Exploratory Discussion
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DSA/Problem Solving & Coding Assessment
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System Design Interview
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Product Interview
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Technical and Cultural Fit
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Compensation Discussion
Important Note
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