AI Engineer

• Own the complete lifecycle of large language model implementation: from data preparation and fine-tuning through rigorous evaluation and production deployment
• Develop automated evaluation frameworks that continuously assess model accuracy, identify edge cases, and quantify improvements across iterations
• Work directly with product managers and engineers to integrate AI as a core product capability
• Shape our AI roadmap by staying current with industry developments, evaluating emerging techniques, and making pragmatic adoption decisions
• Design and implement low-latency, high-throughput, cloud-based AI/ML systems capable of handling thousands of requests per second
• Build the foundational infrastructure - model serving, monitoring, deployment pipelines, and automated testing frameworks - that enables rapid experimentation and iteration while maintaining production reliability

• 5-7+ years of engineering experience with demonstrated hands-on knowledge of applying LLMs and agents in industry
• Experience at a high-growth startup building machine learning infrastructure from the ground up
• Demonstrated ability to take models from research/experimentation through production deployment at scale
• Fluency in Python and related AI/ML frameworks (TensorFlow, PyTorch, Keras, etc.)
• Hands-on experience with LLMs and contemporary AI engineering patterns: RAG architectures, embedding models, vector databases, prompt engineering, and fine-tuning strategies
• Curious, systematic, and execution-oriented—you don't wait for perfect requirements and can navigate technical tradeoffs independently
• Strong foundation in MLOps: CI/CD for ML, model versioning, monitoring, and observability
• Strong technical background in AWS cloud architecture and automated infrastructure provisioning with Terraform

Experience with agentic frameworks like langchain is a plus

• Offers Equity
• competitive salary
• generous benefits
• a 401k match