Senior Enterprise AI Engineer

About Wasabi Technologies

At Wasabi, we’re a proven collection of pioneers, visionaries and disruptive doers. We see things differently than our competitors, and we make our mark in the industry by challenging the norm and delivering the unexpected and improbable. We’re a fast-growing company taking the Cloud Storage industry by storm and recognized as one of the best places to work in Boston.

Wasabi hot cloud storage is a new class and category of cloud storage, breaking all traditional barriers and boundaries of storage with a disruptive value proposition of being dramatically lower cost than legacy hyperscalers, faster than the competition, with no fees for egress or API requests. Cloud storage has never been so simple, so fast and so inexpensive. It’s all part of our vision to make cloud storage the next great global utility, just like electricity.

Role Purpose

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.

Responsibilities

• 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.

Requirements

• 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.

Nice to Have

• BS in CS/ML or related field, or equivalent practical experience.
• Experience with security and privacy controls for AI systems (PII handling, access control, guardrails, auditability).
• Experience working with distributed systems and large-scale data platforms.