Software Developer with AI / Java

Role & responsibilities:

Job Requirements (Skills)

• Experience with application of AI to software development patterns and processes to transform the way teams build products at scale
• A minimum of 7 years of professional experience in production applications development in Java ecosystems including front-end development (preferrably React) and DevOps activities with a strong ability to troubleshoot, resolve, and prevent issues in a high-pressure environment.
• Proficiency in Java and Web API development, with a solid understanding of building and maintaining scalable, secure, and efficient backend services.
• Strong, hands-on experience with React, with a focus on building dynamic, interactive, and high-performance web applications.
• Expertise in database design and SQL skills, particularly with SQL Server, including advanced T-SQL scripting, query optimization, and performance tuning.
• Comprehensive experience in a DevOps activities like continuous integration, continuous delivery
• Experience with the Software Development Life Cycle (SDLC), including requirements gathering, design, development, testing, deployment, and maintenance.
• Exceptional problem-solving skills and a keen attention to detail, ensuring high-quality deliverables and efficient resolution of complex technical challenges.
• Hands-on experience with agentic AI frameworks such as LlamaIndex, Pydantic-AI, LangChain, or similar.
• Proficiency in designing and implementing RAG pipelines, knowledge graphs, and context-aware agent architectures.
• Strong programming skills in Python and familiarity with relevant libraries (e.g., FastAPI, Pydantic, OpenAI API).
• Experience with observability and evaluation tools for AI agents, such as Phoenix and Ragas, including setting up monitoring dashboards and performance metrics.
• Solid understanding of prompt engineering, memory management, and agent orchestration patterns.
• Familiarity with cloud platforms (AWS, Azure, GCP) and deploying agentic solutions in production environments.
• Strong analytical, troubleshooting, and communication skills, with the ability to explain complex agentic concepts to diverse stakeholders.
• Commitment to responsible AI practices, including transparency, fairness, and compliance with regulatory standards