15 Job Overview We are seeking experienced AI Software Engineers with strong Java development experience and hands-on expertise in Agentic AI and the AI Development Life Cycle (AIDLC ) to build next-generation AI-powered applications and platforms. The ideal candidate will have 10+ years of software engineering experience, strong hands-on Java experience, and proven experience developing, deploying, and supporting production-grade Generative AI and Agentic AI solutions across the AI Development Life Cycle. What You'll Do Design, develop, test, deploy, and maintain scalable AI-powered applications using Java Work across the AI Development Life Cycle (AIDLC), including AI solution design, development, testing, evaluation, deployment, monitoring, and continuous improvement Build and integrate AI agents and Agentic AI workflows for enterprise applications Develop and optimize RAG architectures and knowledge retrieval pipelines Integrate LLMs such as OpenAI, Claude, Gemini, Llama, and similar models Develop AI agent orchestration using LangGraph, LangChain, LlamaIndex, CrewAI, AutoGen, or similar frameworks Design and develop Java-based APIs, microservices, and cloud-native applications Implement vector databases and semantic search solutions Build intelligent assistants and AI-driven workflow automation Establish AI evaluation, guardrails, monitoring, observability, security, and governance Analyze AI application performance and continuously improve model, prompt, retrieval, and agent workflows Collaborate with architects, product teams, data scientists, and engineering teams to deliver enterprise AI solutions Required Qualifications 10+ years of professional software engineering experience 10+ Years of experience on Java development experience Mandatory Strong hands-on Java development experience Mandatory Hands-on Agentic AI / AI Agent development Mandatory Experience with
AIDLC / AI
Development Life Cycle Mandatory Hands-on experience building production-grade Generative AI applications Experience with: OpenAI, Claude, Gemini, Llama, or similar LLMs LangGraph, LangChain, LlamaIndex, CrewAI, AutoGen, or similar frameworks RAG architectures and vector databases such as Pinecone, Weaviate, Qdrant, Chroma, or Milvus Strong experience with REST APIs, microservices, and distributed systems Experience with AWS, Azure, or Google Cloud Platform Strong understanding of software engineering, debugging, testing, and code reviews Experience deploying and supporting AI applications in production environments
