Senior Platform Software Engineer - Java Fullstack
Summary
Builds secure, cloud-native Java full-stack apps and integrates AI features like LLMs, RAG, and agents into enterprise systems using Spring Boot, microservices, and modern DevOps.
The successful candidate will have strong fundamentals in software engineering, data structures and algorithms, and experience designing secure, scalable, cloud-native applications. Exposure to AI/ML, Retrieval-Augmented Generation (RAG), AI agents, and enterprise AI platforms is highly desirable.
Required Qualifications
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Bachelor's or Master's degree in Computer Science or a related field from a reputed university.
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5+ years of experience designing and developing scalable, distributed enterprise applications.
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Strong expertise in Java, J2EE, Spring Boot, microservices, REST APIs, and modern web technologies.
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Experience with JavaScript, Node.js, Oracle JET (or similar UI frameworks), Git, Docker and CI/CD pipelines.
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Strong understanding of data structures, algorithms, design patterns, and scalable system architecture.
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Experience building, deploying, and operating cloud-native applications on OCI, AWS, Azure, or Google Cloud.
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Hands-on experience using AI-powered software development tools such as ChatGPT Codex or similar coding assistants to improve engineering productivity.
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Exposure to enterprise AI technologies including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, AI agents, prompt engineering, and AI application integration is highly preferred.
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Strong analytical and problem-solving skills with the ability to design innovative, scalable solutions.
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Excellent communication, collaboration, and technical leadership skills.
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Passion for continuous learning and adopting emerging AI technologies and engineering best practices.
Responsibilities
- Design, develop, and deliver highly scalable, secure, cloud-native enterprise applications using Java and modern full-stack technologies.
- Build AI-enabled enterprise capabilities by integrating Large Language Models (LLMs), AI services, intelligent agents, and enterprise knowledge retrieval into business applications.
- Design and implement RESTful APIs, microservices, and event-driven architectures following modern engineering best practices.
- Leverage AI-assisted development tools to improve code quality, accelerate development, automate testing, documentation, and code reviews.
- Evaluate, prototype, and implement emerging AI technologies to improve developer productivity and enhance customer experiences.
- Develop AI-powered features such as intelligent search, conversational interfaces, workflow automation, recommendation engines, and natural language interactions.
- Apply architecture patterns and engineering best practices to ensure scalability, performance, security, reliability, and maintainability.
- Participate in technical design reviews, code reviews, architecture discussions, and mentoring of engineering teams.
- Support issue analysis, debugging, performance optimization, and production incident resolution.
- Thrive in a fast-paced, collaborative, and globally distributed engineering environment while delivering high-quality outcomes.
Career Level - IC3