Senior Java Developer – Agentic AI
The Senior Java Developer – Agentic AI is responsible for designing, developing, and deploying intelligent, autonomous applications by combining modern Java backend technologies with Agentic AI and Generative AI capabilities. The role focuses on building scalable microservices, integrating Large Language Models (LLMs), developing AI agent workflows, and delivering cloud-native enterprise solutions.
- Design and develop scalable backend applications using Java, Spring Boot, and Microservices.
- Build and implement AI agent workflows and multi-agent systems.
- Integrate Large Language Models (LLMs) and Generative AI capabilities into enterprise applications.
- Develop RESTful APIs and event-driven architectures for AI-powered applications.
- Build and deploy cloud-native solutions on Azure and/or AWS.
- Collaborate with AI engineers, product teams, and solution architects to deliver intelligent solutions.
- Optimize application performance, scalability, security, and reliability.
- Participate in architecture discussions, code reviews, and technical design.
- Implement best practices for AI integration, software development, and DevOps.
- Ensure high-quality code through testing, debugging, monitoring, and continuous improvement.
- Strong hands-on experience in Java, Spring Boot, and Microservices.
- Experience with Agentic AI, AI Agents, or Generative AI solutions.
- Knowledge of Large Language Models (LLMs) and AI integration patterns.
- Experience building REST APIs and distributed systems.
- Hands-on experience with Kafka or other event-driven messaging platforms.
- Experience with Azure and/or AWS cloud platforms.
- Strong understanding of API integration and enterprise application development.
- Knowledge of software design principles, SDLC, and Agile methodologies.
- Strong debugging, troubleshooting, and performance optimization skills.
- Excellent communication and problem-solving abilities.
- Experience designing and orchestrating multi-agent AI systems.
- Knowledge of AI safety, guardrails, and human-in-the-loop workflows.
- Experience with prompt engineering, prompt tuning, and model evaluation.
- Exposure to AI observability and monitoring frameworks.
- Experience with Vector Databases, RAG (Retrieval-Augmented Generation), and AI orchestration frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or Semantic Kernel.
- Familiarity with Docker, Kubernetes, and CI/CD pipelines.
- Experience with Azure AI Services, Azure OpenAI, AWS Bedrock, or OpenAI APIs.
- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or equivalent experience.
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