Senior Enterprise AI Engineer, Wasabi

• 5+ years of experience in software engineering or applied AI/ML engineering, with experience building production services
• Demonstrated ability to design and deliver AI/ML-powered applications and/or platform capabilities in real-world environments
• Solid understanding of core AI concepts and modern Generative AI patterns (RAG, prompt engineering, evaluation, agentic workflows)
• Experience with the AI lifecycle: data pipelines, training/fine-tuning (where applicable), evaluation, deployment, and monitoring
• Proficiency in one or more of: Python, Go, Java, or similar languages with strong fundamentals in APIs, reliability, observability, and performance
• Experience with modern AI/ML frameworks (e.g., PyTorch, TensorFlow, JAX) and cloud AI/ML platforms (AWS, GCP, Azure)
• Strong communication skills and the ability to work effectively with technical and non-technical stakeholders

Desirable

• Wasabi is seeking an AI Engineer to help build and scale our Enterprise AI Platform
• This platform will be the foundation that enables AI assistants, agents, and AI-powered applications across Wasabi’s business functions
• In this role, you’ll be a hands-on engineer who can translate business needs into concrete AI solution designs, implement core platform and application components, and drive solutions into production with measurable impact
• You’ll operate at the intersection of AI innovation, software engineering, and business operations
• You will partner closely with stakeholders across Sales, Marketing, Finance, HR, Legal, Customer Support, and IT to deliver secure, reliable, and scalable AI capabilities that elevate productivity and decision-making across the company
• Design and implement AI-powered solutions (assistants, agents, and apps) that solve business problems across enterprise functions
• Build platform capabilities for modern AI workloads, including retrieval-augmented generation (RAG), agent orchestration, evaluation, and production inference services
• Implement scalable services that support low-latency, high-throughput AI applications, while meeting reliability, security, and cost objectives
• Develop reusable patterns, libraries, and best practices that enable teams to safely and efficiently build on the Enterprise AI Platform
• Support rapid experimentation (POCs), evaluate emerging AI tools/frameworks, and help evolve platform architecture to incorporate successful innovations into production
• Contribute to MLOps pipelines (training, fine-tuning, versioning, deployment, monitoring, drift detection) to streamline the model lifecycle
• Help define and implement automated testing strategies for AI solutions (quality, safety, regression, hallucination checks, latency, and robustness)
• Partner with Data/Analytics, Security, IT, and Engineering teams to ensure strong data governance, privacy protections, and responsible AI practices
• Contribute to team engineering excellence through code reviews, documentation, and knowledge-sharing