What you will do ?

- Design and implement generative AI solutions using large language models (LLMs).

- Apply prompt engineering techniques and build scalable Retrieval-Augmented Generation (RAG) systems.

- Fine-tune and optimize models for performance, cost, and reliability.

- Leverage AWS services such as Bedrock, SageMaker, and Lambda for deployment and inference.

- Develop APIs and backend components for production-grade AI applications.

- Implement observability, performance monitoring, and security best practices.

- Drive responsible AI adoption through evaluation, bias detection, and compliance.

What are we looking for ?

- 3+ years of experience in Python with strong software engineering fundamentals.

- Hands-on experience with LLMs and prompt engineering strategies.

- Experience designing RAG pipelines and working with vector databases.

- Proficiency in model fine-tuning (e.g., LoRA) and embedding-based systems.

- Experience with cloud platforms and deploying AI models in production.

- Strong debugging, optimization, and problem-solving skills.

- Clear and effective technical communication.

- Production-first mindset with attention to cost, reliability, and performance.

Preferred Qualifications :

- Practical experience with frameworks like LangChain or LlamaIndex.

- Exposure to multi-modal AI systems.

- Familiarity with ML/MLOps and large-scale deployment practices.

- Experience supporting systems at high request volumes.