AI Engineer

Key Responsibilities

• Build Production AI Systems: Design, develop, and deploy robust AI applications using LLMs, including prompt engineering, agent workflows, tool use, and full-stack AI products
• Work Directly with Customers: Partner closely with enterprise stakeholders to understand complex problems and translate them into impactful AI solutions
• Lead System Architecture: Design scalable architectures for production AI systems, balancing performance, reliability, cost, and maintainability
• Develop Our Internal Platform: Contribute to Distillery, our internal LLM application platform, by building reusable infrastructure, tools, and workflows used across customer deployments
• Evaluate AI Systems Rigorously: Develop evaluation frameworks that measure model performance across accuracy, latency, cost, reliability, and safety
• Ship Production-Grade Systems: Ensure systems meet high standards for observability, reliability, security, and maintainability
• Raise the Engineering Bar: Improve development workflows, evaluation practices, and deployment strategies as our AI platform continues to evolve

Who You Are

• 3+ years of professional software engineering experience
• Strong proficiency in Python or TypeScript
• Experience building and deploying LLM-powered applications or AI agents in production
• Experience with modern LLM tooling such as LangChain, LlamaIndex, Guardrails, MCP, or agent frameworks
• Experience implementing RAG pipelines, tool use, or multi-step AI workflows
• Strong understanding of AI system evaluation, debugging, and observability
• Experience building reliable production systems with modern DevOps practices
• Experience deploying AI systems in enterprise environments is a plus
• Experience working across cloud platforms (AWS, GCP, or Azure) is a plus
• Experience with agent architectures and long-horizon task execution is a plus
• Familiarity with responsible AI practices, including auditability and governance is a plus