AI Engineer

• As an AI Engineer focused on Generative Systems & Automation, you will have end-to-end ownership of the AI services that power our business. Your responsibilities will span the full lifecycle, from system architecture to operational excellence.
• Architect Advanced Generative AI Systems: Design and deploy autonomous AI agents that can reason, plan, and execute complex business processes by interacting with internal APIs and toolsets using function calling and MCP servers.
• Leverage both open-source and proprietary Large Language Models (LLMs) to create specialized agentic systems that are optimized for our unique domain challenges in terms of performance, cost, and accuracy.
• Architect, build, and optimize end-to-end Retrieval-Augmented Generation (RAG) systems, employing advanced techniques like query transformation, hybrid search, and re-ranking to ground our LLMs in proprietary business data (e.g., product catalogs, customer interactions, supply chain data).
• Master End-to-End Productionization (LLMOps): Implement comprehensive observability and monitoring for our AI systems, tracking not only performance metrics (latency, throughput) but also qualitative behaviors like model drift, hallucinations, and response quality using platforms like Langfuse or Datadog.
• Own the full LLMOps lifecycle for our generative AI services, including building robust CI/CD pipelines for automated testing and deployment using tools like Docker and Kubernetes.
• Establish and manage rigorous evaluation frameworks using both automated metrics and LLM-as-a-judge methodologies to ensure our systems meet the highest standards of quality and reliability.
• Proactively manage and optimize the cost-efficiency of our AI systems by implementing strategies such as intelligent model routing, response caching, and prompt optimization.

AI Engineer

Lead AI Engineer