SDE III (Backend)

We are looking for an experienced Backend Engineer with deep expertise in LLMs, agentic AI, and agent lifecycle development, plus hands-on experience with Java and Spring Boot. The ideal candidate should have experience building scalable backend systems and integrating AI capabilities into production-grade applications. Candidates with experience in Java, Python, Go, or Ruby are welcome, provided they are willing to work with Java and Spring Boot.

Responsibilities:

• Design, develop, and maintain scalable backend services using Java, Spring, and Spring Boot.
• Build and integrate LLM-powered applications, AI agents, and agentic workflows.
• Work across the complete agent lifecycle, including planning, tool calling, execution, memory management, orchestration, monitoring, and evaluation.
• Develop APIs and backend services to integrate LLMs with enterprise applications, databases, and external tools.
• Implement agentic AI architectures to support multi-step reasoning, task automation, and autonomous decision-making.
• Optimize backend performance, scalability, reliability, and security for production environments.
• Collaborate with cross-functional teams to design and deploy AI-powered solutions.
• Troubleshoot, test, and continuously improve AI-driven backend applications.

Requirements:

• Strong software engineering experience with Java, Python, Go, or Ruby, with a willingness to work extensively with Java.
• Hands-on experience with Spring Framework and Spring Boot.
• Practical experience working with Large Language Models (LLMs) and building LLM-powered applications.
• Strong experience in Agentic AI, including developing and implementing AI agents and agentic workflows.
• Understanding of the agent lifecycle, including planning, tool use, execution, orchestration, memory, and evaluation.
• Experience integrating AI models and services into backend applications.
• Strong understanding of REST APIs, microservices, data structures, and software design principles.
• Experience building, testing, and deploying production-ready applications.

Preferred Qualifications:

• Experience with LLM orchestration frameworks and agent development tools.
• Familiarity with RAG (Retrieval-Augmented Generation), vector databases, embeddings, and prompt engineering.
• Experience with multi-agent systems, tool calling, and workflow orchestration.
• Knowledge of cloud platforms, containerization, and CI/CD practices.
• Experience monitoring and evaluating LLM applications in production.

Ideal Candidate Profile:

• A hands-on engineer who combines strong backend development fundamentals with practical LLM and Agentic AI experience.
• The candidate should be comfortable working across the AI agent lifecycle and willing to build backend services in Java using Spring and Spring Boot.
• Must-have skills: LMs, Agentic AI, Agent Lifecycle, Spring, Spring Boot, and proficiency in Java/Python/Go/Ruby, with willingness to work on Java.