Senior Agentic AI Engineer

About the Role

Join a dynamic team at An Engineering company, where you will play a pivotal role in transforming the way researchers collaborate and publish their findings. You will work closely with a talented group of professionals dedicated to solving critical challenges in the academic space. This position offers significant opportunities for growth and impact within an innovative startup environment that is rapidly advancing in the technology industry.

Responsibilities

• Design, develop, and maintain scalable and efficient machine learning systems, including writing ML services and APIs.
• Implement and manage the deployment of machine learning models, specifically transformer-based LLMs, in production environments while ensuring reliability and scalability.
• Collaborate with infrastructure teams to optimize and manage underlying systems that support machine learning workflows.
• Create robust and efficient data pipelines for collecting, processing, and preparing datasets for machine learning models.
• Work closely with data scientists, researchers, and cross-functional teams to effectively integrate ML solutions into existing software infrastructure.
• Continuously optimize and enhance the performance of machine learning algorithms and systems.
• Develop and maintain comprehensive documentation for machine learning systems, APIs, and data pipelines to facilitate ease of use within the team.

Requirements

• At least 3 years of experience in designing multi-component systems.
• Proficient in one high-level programming language, preferably Python.
• General understanding of SQL and database design concepts.
• Solid knowledge of testing fundamentals in software development.
• Excellent communication skills for effective collaboration across teams.
• Demonstrated experience in managing and executing technology products.
• Familiarity with various Gen AI based ML approaches.
• Experience in building agentic architectures using langgraph or similar libraries.

Nice to Have

• +Prior experience with high-volume, always-available web applications.
• +Experience working in cloud environments.
• +Knowledge of cloud platforms such as AWS, GCP, or Azure.
• +Experience deploying small and large open source LLMs in production using containerization tools like Docker.
• +Background in distributed systems development.