Senior Product Development AI Engineer

We are seeking a Senior Product Development AI Engineer with deep expertise in enterprise Java application development and hands-on experience integrating AI into the Software Development Life Cycle (SDLC). The ideal candidate will lead the design and development of scalable Java applications while driving AI adoption across development, testing, code quality, automation, and engineering productivity. Experience building or integrating AI-powered applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), or AI frameworks is highly desirable.

Key Responsibilities 

• Lead the architecture, design, and development of enterprise-grade Java applications. 

• Design and implement scalable microservices using Java, Spring Boot, and REST APIs. 

• Drive technical leadership across multiple engineering teams and mentor senior developers. 

• Integrate AI tools into the SDLC to improve developer productivity, code quality, testing, and documentation. 

• Leverage AI-assisted development tools such as GitHub Copilot, ChatGPT, Cursor, Claude, or similar platforms. 

• Build AI-enabled features using LLMs, prompt engineering, vector databases, and RAG architectures where applicable. 

• Establish engineering best practices for secure, scalable, and maintainable software development. 

• Collaborate with product managers, architects, DevOps, QA, and data engineering teams. 

• Lead code reviews, performance optimization, and production support activities. 

• Define technical roadmaps and guide modernization initiatives. 

• Drive CI/CD automation and cloud-native development practices. 

• Ensure application security, observability, and compliance with enterprise standards. 

Required Skills 

• 5+ years of Core Java development experience. 

• Strong expertise in Java , Spring Boot, Spring MVC, Spring Security, and Spring Data. 

• Extensive experience with Microservices architecture. 

• Strong understanding of multithreading, concurrency, JVM tuning, and performance optimization. 

• Experience with RESTful APIs, and messaging technologies. 

• Strong SQL and NoSQL database experience (Oracle, PostgreSQL, MongoDB, Cassandra, Redis). 

• Experience with Docker, Kubernetes, and containerized deployments. 

• Hands-on experience with AWS, Azure, or Google Cloud Platform. 

• Strong knowledge of CI/CD pipelines using Jenkins, GitHub Actions, GitLab CI, or Azure DevOps. 

• Experience with Git, Maven, Gradle, SonarQube, Nexus, and Artifactory. 

• Strong knowledge of software design patterns and clean architecture. 

AI & AI-Enabled SDLC Experience 

• Experience using AI tools throughout the SDLC, including: 

• AI-assisted coding 

• Automated unit test generation 

• Code reviews 

• Documentation generation 

• Refactoring 

• Bug analysis 

• Root cause analysis 

• Security scanning 

•  experience with: 

• Large Language Models (LLMs) 

• Prompt Engineering 

• Retrieval-Augmented Generation (RAG) 

• AI Agents 

• MCP (Model Context Protocol) concepts 

• Vector databases 

• LangChain, LangGraph, LlamaIndex, or similar AI frameworks 

• OpenAI, Anthropic, Azure OpenAI, or Google Vertex AI 

Nice to Have 

• Experience with Generative AI application development. 

• Knowledge of agentic AI architectures. 

• Experience with semantic search and vector embeddings. 

• Exposure to AI governance, compliance, and responsible AI frameworks.