- Design, develop, and deploy robust and scalable AI/ML solutions primarily utilizing AWS Bedrock and its supported models (e.g., Claude, Titan, Cohere, Mistral).

- Implement and optimize Bedrock Agents, focusing on orchestration and designing efficient agent workflows to automate complex tasks.

- Develop high-quality, maintainable code using Python, .Net, or another backend programming language, adhering to best practices and architectural patterns.

- Work extensively with Large Language Models (LLMs), including advanced prompt engineering techniques, generating and utilizing embeddings, and integrating with vector databases (e.g., FAISS, Pinecone, Amazon OpenSearch) for efficient similarity search.

- Architect and implement Retrieval Augmented Generation (RAG) solutions and advanced semantic search capabilities to enhance LLM responses with relevant external data.

- Apply LLMOps practices to manage the lifecycle of LLMs, from experimentation and fine-tuning to deployment, monitoring, and continuous improvement.

- Utilize a deep understanding of core AWS services such as Lambda, IAM, API Gateway, S3, DynamoDB, and CloudWatch to build secure, efficient, and observable applications.

- Collaborate effectively with cross-functional teams, including product managers, data scientists, and other engineers, to translate business requirements into technical specifications and deliver innovative solutions.

- Stay abreast of the latest advancements in LLMs, generative AI, and AWS Bedrock features, proactively recommending and integrating new technologies to maintain a competitive edge.

- Troubleshoot and resolve complex technical issues related to LLM integration, Bedrock services, and overall system performance.

Whats in it for you?

Join an ever-growing, market disrupting, global company where the teams comprised of the best of the best work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NICE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations.