Software Engineer (Java/Go with AI)

• Design, develop, test, and maintain scalable backend and frontend
• components for enterprise-grade SaaS applications.
• Translate product and business requirements into clear technical designs and implementation plans.
• Contribute to system and API design, ensuring maintainability, performance, and scalability.
• Write high-quality, we’ll-documented, and testable code following best practices.
• Participate in peer code reviews and provide constructive feedback.
• Collaborate effectively with cross-functional and multi-region teams to
• deliver features within agreed timelines.
• Support and improve existing systems through refactoring, optimization, and bug fixes.
• Follow Agile development practices and contribute to continuous
• improvement of engineering processes.

Requirements

• 3-6 years of professional software development experience.
• Strong programming skills in Java, Python, Go, or Rust.
• Solid experience building backend systems using modern frameworks and libraries.
• Hands-on experience with API frameworks and protocols such as REST, WebSockets, gRPC, and familiarity with MCP.
• Practical experience with relational or document databases such as Postgres or MongoDB.
• Strong understanding of microservices-based architectures and distributed systems fundamentals.
• Solid foundation in data structures, algorithms, and system design.
• Experience building or integrating LLM-based features, including RAG (Retrieval-Augmented Generation) and vector search.
• Familiarity with agent frameworks such as LangChain, LangGraph
• Experience working with distributed or multi-region teams.
• Strong analytical and problem-solving skills, with attention to detail and code quality.

Good to Have

• Experience with messaging and data infrastructure such as Kafka, Redis, and ClickHouse.
• Hands-on experience working in Linux environments.
• Experience with both relational and NoSQL databases.
• Exposure to multiple data paradigms: SQL, NoSQL, time-series, or graph databases.
• Experience deploying and operating AI/ML or LLM-powe’red services (MLOps / LLMOps).
• Familiarity with observability for AI systems, including logging, tracing, monitoring, and evaluation.
• Exposure to LLM fine-tuning techniques such as LoRA, QLoRA, or instruction tuning

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