AI Engineer

• Design and implement AI platforms enabling scalable, secure access to LLMs from multiple model providers.
• Design and implement agentic workflows, tool ecosystems, and LLM prompt management solutions.
• Design, build, and optimize scalable model training, fine tuning, and inference pipelines integrated with production systems.
• Influence technical strategy for embedding stores, vector databases, and reusable assets.
• Lead initiatives to streamline ML/AI workflows, improve operational efficiency, and establish standardized procedures.
• Design and develop backend services and RESTful APIs using Python and FastAPI integrated with ML pipelines.
• Take operational responsibility for team-owned services including monitoring, optimization, troubleshooting, and on-call rotation.
• Collaborate with data and applied scientists, software engineers, product managers, and stakeholders to deliver ML-driven products.
• Coach and mentor ML engineers, promoting collaboration and engineering excellence.
• Build, deploy, and maintain ML infrastructure using AWS, Databricks, Docker, Kubernetes, Terraform, Snowflake, Coralogix, and GitHub.

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