Sr AI Engineer

WEX•Seattle, WA

1d•Remote

About The Position

We are a fast-growing AI Engineering team, driving WEX's strategic vision to integrate artificial intelligence into the core of our product and business. Our team thrives on collaboration, working directly with stakeholders and domain experts to develop innovative AI platforms and solutions that enhance decision-making and create groundbreaking products that benefit our customers and help them to effectively grow their business. We foster a culture of continuous learning and believe that the best work stems from a shared purpose and an enjoyable, engaging environment. You are an experienced technical leader and subject matter expert with a deep passion for AI, Machine Learning, and software engineering. You possess a proven track record of architecting scalable systems and solving complex ambiguity using data-driven tools. You will act as a force multiplier for the team—setting technical standards, mentoring junior engineers, and partnering with product leadership to turn abstract business goals into production-grade AI solutions.

Requirements

5+ years of experience as an AI/ML Engineer, Data Scientist, or Software Engineer with a heavy focus on production ML systems.
Bachelor's degree in Computer Science, Software Engineering, or related field; a Master’s or PhD in AI/ML is preferred.
Production expertise: Proven track record of taking AI solutions from concept to high-scale production using Java, C#, GoLang, or Python.
LLM Proficiency: Deep experience with Generative AI, including prompting strategies, RAG (Retrieval-Augmented Generation), fine-tuning, and agentic workflows.
System Design: Strong ability to design distributed systems and microservices architectures for model serving.
Collaboration: Demonstrated ability to lead technical discussions with non-technical stakeholders and drive consensus.
Expert proficiency in Python (preferred) or other core languages (Java, Go, C#).
Deep knowledge of modern ML frameworks (PyTorch, TensorFlow, Scikit-learn) and LLM orchestration (LangChain, LlamaIndex, vLLM).
Advanced understanding of MLOps principles, feature stores, and model monitoring.
Solid grasp of advanced probability, statistics, and linear algebra.
Extensive hands-on experience with Kubernetes (deploying and managing clusters) and Cloud platforms (AWS preferred).
Strong command of CI/CD methodologies and Infrastructure as Code (Terraform).
Excellent data engineering skills (SQL, NoSQL, data lakes, and processing pipelines).

Nice To Haves

Experience in the financial or fintech industry is a plus.

Responsibilities

Technical Strategy & Architecture: Partner with stakeholders to translate complex customer challenges into robust technical designs and AI strategies.
End-to-End Ownership: Architect, build, and deploy high-performance AI/ML platforms and tools, ensuring scalability, reliability, and security.
Advanced Model Development: Lead the development, evaluation, fine-tuning, and monitoring of production-grade AI/ML models (including LLMs and RAG architectures).
Operational Excellence: Design and standardize CI/CD pipelines (GitHub Actions) and Infrastructure as Code (Terraform) to ensure reproducible and automated deployments.
Reliability & Scale: Proactively monitor system health, lead incident response for critical AI systems, and drive architectural refactoring to remove bottlenecks.
Mentorship: Mentor L1/L2 engineers, conduct code reviews, and foster a culture of engineering excellence and best practices.
Innovation: Evaluate emerging AI technologies/vendors and prototype new approaches to keep the organization at the cutting edge of the industry.