Key Responsibilities:

- Design, develop, and deploy AI-powered applications using Java and AWS.

- Architect and implement robust Retrieval-Augmented Generation (RAG) solutions for enterprise use cases.

- Integrate and optimize Large Language Models (LLMs) for production environments.

- Develop effective prompt engineering strategies to improve AI model performance and accuracy.

- Build scalable, secure, and high-performing AI services leveraging AWS cloud technologies.

- Collaborate with business stakeholders and engineering teams to translate business requirements into AI-driven solutions.

- Evaluate, optimize, and monitor AI models for performance, reliability, and scalability.

- Stay up to date with emerging trends in Generative AI, LLMs, and cloud technologies.

Required Skills & Qualifications:

Must-Have Skills:

- Strong proficiency in Java.

- Hands-on experience with Large Language Models (LLMs).

- Strong expertise in Prompt Engineering.

- Proven experience designing and implementing Retrieval-Augmented Generation (RAG) architectures.

- Hands-on experience with the AWS Cloud Platform.

- Strong analytical, troubleshooting, and problem-solving skills.

- Ability to explain complex technical concepts to both technical and non-technical stakeholders.

- Experience building scalable, production-ready AI applications.

Nice-to-Have Skills:

- Experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.

- Knowledge of MLOps practices, tools, and deployment pipelines.

- Familiarity with AI model lifecycle management, monitoring, and optimization.

- Exposure to enterprise AI governance and best practices.