Staff AI Engineer (L4)
WEX
hybridleadpermanentbackendengineering-management Maine, United States Yesterday via LinkedIn
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PythonMLOpsLLMRAGKubernetesTerraformCI/CDDistributed SystemsPyTorchLangChain
About the role
Role Overview
Staff AI Engineer (L4) at WEX. You will be a technical leader and AI/ML subject matter expert, partnering with stakeholders and product leadership to turn business goals into scalable, production-grade AI solutions.
Responsibilities
- Technical Strategy & Architecture: Translate complex customer challenges into technical designs and AI strategies.
- End-to-End Ownership: Architect, build, and deploy high-performance AI/ML platforms and tools (scalability, reliability, security).
- Advanced Model Development: Lead development, evaluation, fine-tuning, and monitoring of production AI/ML models, including LLMs and RAG.
- Operational Excellence: Standardize CI/CD pipelines using GitHub Actions and use Infrastructure as Code with Terraform for automated, reproducible deployments.
- Reliability & Scale: Monitor system health, lead incident response for critical AI systems, and refactor architectures to remove bottlenecks.
- Mentorship: Mentor L1/L2 engineers, conduct code reviews, and promote engineering best practices.
- Innovation: Evaluate emerging AI technologies/vendors and prototype new approaches.
Requirements
- 8+ years experience as an AI/ML Engineer, Data Scientist, or Software Engineer with a focus on production ML systems.
- Bachelor’s degree in CS/Software Engineering (Master’s or PhD in AI/ML preferred).
- Proven ability to take AI solutions from concept to high-scale production using Java, C#, Go, or Python.
- Strong Generative AI experience: prompting, RAG, fine-tuning, and agentic workflows.
- Ability to design distributed systems and microservices for model serving.
- Experience leading technical discussions with non-technical stakeholders.
Nice to Have
- Experience in financial/fintech.
Technical Skills
- Python (preferred); also Java, Go, C#.
- ML frameworks: PyTorch, TensorFlow, Scikit-learn.
- LLM orchestration: LangChain, LlamaIndex, vLLM.
- MLOps: feature stores, model monitoring.
- Probability/statistics and linear algebra.
- Kubernetes cluster deployment/management.
- Cloud platforms, AWS preferred.
- CI/CD and Terraform.
- Data engineering: SQL, NoSQL, data lakes, processing pipelines.
About WEX
WEX is a company in the financial services and payments domain, building products that support businesses’ growth. They have a fast-growing AI Engineering team focused on integrating AI into the core of their product and business to improve decision-making and customer outcomes.
Scraped 8/5/2026