Senior Software Engineer (Java)

TL;DR

Senior Software Engineer (Java): Building and operating high-performance backend services for enterprise AI products with an accent on distributed systems, production reliability, and API design. Focus on integrating applications with machine learning models, ensuring low-latency performance, and maintaining high availability through robust observability and testing practices.

Company

hirify.global is a global provider of enterprise AI products and services dedicated to democratizing AI through high-quality education and scalable enterprise solutions.

What you will do

• Design, build, and maintain scalable backend services and microservices using Java.
• Develop reliable model-calling workflows with appropriate validation, retries, and fallback behaviors.
• Implement resilience patterns including caching, circuit breakers, and rate limiting.
• Monitor system performance, latency, and availability using tools like Datadog.
• Develop comprehensive unit, integration, and performance tests to ensure production reliability.
• Participate in architecture reviews, incident response, and root-cause analysis.

Requirements

• Strong professional experience developing production applications with Java.
• Deep understanding of distributed systems, design patterns, and software architecture.
• Experience building systems with demanding availability, scalability, and latency requirements.
• Proficiency in implementing production logging, monitoring, and alerting.
• Familiarity with cloud platforms, containers, and modern deployment environments.
• Basic understanding of machine learning concepts and model interaction.

Nice to have

• Experience with Kafka, message queues, or event-driven architectures.
• Experience with Kubernetes, Redis, or distributed caching.
• Background in advertising technology, recommendation systems, or real-time decisioning.
• Experience with AI-assisted development tools like GitHub Copilot or Cursor.

Culture & Benefits

• Opportunity to work on global enterprise AI transformation projects.
• Collaborative environment working across software, machine learning, and infrastructure teams.
• Commitment to diversity, inclusion, and democratizing AI education.
• Focus on strong software engineering practices and production reliability.