Wasabi Technologies is a fast-growing company recognized as one of the best places to work in Boston, specializing in innovative cloud storage solutions. They are seeking a Senior Enterprise AI Engineer to build and scale their Enterprise AI Platform, enabling AI applications across various business functions and driving measurable impact through AI innovation and software engineering.
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
- 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