AI/ML Developer with AWS

As a candidate for the position, your main responsibility will involve designing and implementing intelligent Agentic AI systems using LLMs, vector databases, and orchestration frameworks. You will also be tasked with building, deploying, and maintaining ML workflows utilizing AWS SageMaker, Lambda, and EC2 with Docker. Another key aspect of the role will be developing and managing ETL pipelines through AWS Glue and integrating them with structured/unstructured data sources. Additionally, you will be expected to implement APIs and full-stack components to support ML agents, including visualization tools using Streamlit, as well as reverse-engineer existing codebases and APIs to integrate AI features into legacy or proprietary systems. To excel in this role, you must have hands-on experience with AWS services like Lambda, EC2, Glue, and SageMaker. Strong proficiency in Python and full-stack development is essential, along with a solid grasp of LLMs and vector search engines. Demonstrated ability to reverse-engineer systems and build integrations is also required, as well as experience with cloud infrastructure, RESTful APIs, CI/CD pipelines, and containerization. Preferred qualifications for this position include a background in Retrieval-Augmented Generation (RAG), multi-agent systems, or knowledge graphs, experience with open-source LLM frameworks like Hugging Face, knowledge of autonomous task planning, symbolic reasoning, or reinforcement learning, and exposure to secure, regulated, or enterprise-scale AI systems. Overall, this role demands a strong blend of technical skills encompassing AWS, Python, and full-stack development, in addition to expertise with LLMs, vector search, and agentic AI systems.,