Senior AI Engineer

This is a fully remote position, open to applicants in India.

📋 Description

• Design comprehensive AI integration architectures that link LLM APIs, vector databases, and inference systems to the existing backend infrastructure.

• Create reusable machine learning infrastructure components such as feature pipelines, model serving layers, and evaluation frameworks for standardization across multiple portfolio companies.

• Develop best practices and governance patterns for AI system integration that can be replicated as playbooks throughout the holding company.

• Lead system design reviews for AI projects within portfolio companies, pinpointing bottlenecks and suggesting architectural enhancements.

• Enhance production AI systems to optimize for cost and latency by analyzing pipelines, applying compression techniques, and appropriately sizing compute infrastructure.

• Guide engineers in portfolio companies on best practices for production AI, ensuring reproducibility, effective monitoring, and safe deployment methods.

⛳️ Requirements

• A minimum of 5 years of experience in building backend systems or integrations, with practical expertise in connecting various third-party tools and APIs in a production environment.

• A demonstrated ability to architect system integrations at scale that have minimized integration time or standardized tools across teams.

• Proficient in Python and SQL for constructing data pipelines and backend services that support AI systems.

• Practical experience in deploying LLM applications, vector search systems, ML inference pipelines, or automated workflows in a production setting.

• In-depth knowledge of incorporating external AI tools into existing backend architectures without necessitating significant changes to core systems.

• Experience in developing systems that are monitored, version-controlled, and reproducible, rather than one-off prototypes or experimental setups.

• Familiarity with MLOps platforms such as MLflow, Weights & Biases, or SageMaker, along with ML infrastructure tools.

• Knowledge of Kubernetes, Docker, or cloud deployment on AWS, GCP, or Azure for containerizing AI services.

• Experience in building retrieval-augmented generation systems or scaling prompt engineering across teams.

🏝️ Benefits

• Remote work opportunity from India with flexibility regarding location.

• A budget for professional development and attendance at conferences.

• Direct collaboration with multiple portfolio companies to influence how AI is scaled throughout the holding company.