Senior Software Engineer

Job Role: Senior Software Engineer Java + AI

Experience: 4+ Years

Location: Pune(Hybrid)

Job Summary

We are looking for a Senior Software Engineer (Java + AI) with strong expertise in Java backend development, Python-based AI/ML, LLM application development, and distributed systems. The ideal candidate will design and develop scalable production-grade applications integrating LLMs, RAG, and agentic AI frameworks, while providing technical leadership and ensuring engineering best practices.

Key Responsibilities

• Design, develop, and maintain scalable backend services using Java, Spring Boot, and Microservices architecture.

• Develop Python-based AI/ML services, automation scripts, and AI integrations.

• Build and deploy production-grade LLM applications, including:

• LLM API integration

• Prompt engineering and prompt management

• Streaming responses

• Error handling and fallback mechanisms

• Token/cost optimization and monitoring

• Design and implement AI/LLM solutions using LangGraph, LangChain, RAG pipelines, or similar AI orchestration frameworks.

• Build scalable and reliable distributed systems with focus on performance, availability, security, and fault tolerance.

• Implement strong observability through logging, metrics, distributed tracing, monitoring, and alerting.

• Develop and maintain CI/CD pipelines with automated testing, quality gates, and deployment automation.

• Deploy and manage applications on AWS or Azure cloud platforms, leveraging managed AI/ML services where appropriate.

• Participate in system architecture, design reviews, and technical decision-making.

• Mentor junior and mid-level engineers and establish coding, testing, architecture, and engineering standards.

• Collaborate with Product, AI/ML, DevOps, and other engineering teams to deliver high-quality solutions.

• Troubleshoot complex production issues and continuously improve system reliability and performance.

Must-Have Skills

• Java, Spring Boot, Microservices
• Python
• LLM / Generative AI
• LLM API integration and production deployment
• Prompt management, streaming, error handling, and cost optimization
• LangGraph / LangChain / Agentic AI frameworks
• RAG pipelines / AI orchestration
• Distributed systems and scalable backend architecture
• Logging, Metrics, Tracing & Alerting
• CI/CD, Automated Testing, Quality Gates
• AWS or Azure
• Managed AI/ML cloud services
• Technical leadership, mentoring, and design reviews