AI Engineer II

The salary range for this role is $3,333 - $6,000 per month (Gross in USD)

About Sezzle

With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting‑edge tech with seamless, interest‑free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey.

About the Role

We are seeking an experienced and motivated AI Engineer II who possesses a strong blend of technical skill and business insight. This role offers an exciting opportunity to thrive in a fast‑paced environment, with significant prospects for continued growth and ownership.

As a member of the Applied AI team, you will take end‑to‑end ownership of complex platforms and systems that power Sezzle’s AI‑driven capabilities. Your work will span initiatives such as building AI‑powered platforms from scratch, developing intelligent automation and orchestration systems, and embedding proprietary AI solutions directly into customer‑facing products, internal tools, and operational workflows.

What You'll Do

• Lead the design, development, and ownership of AI‑powered internal platforms and systems, including initiatives built from the ground up with a focus on Marketing.
• Own end‑to‑end delivery of complex projects, from problem discovery and system design through production rollout and iteration.
• Design and implement AI‑driven features, intelligent automation, and orchestration systems that enhance customer experiences and compound productivity across teams.
• Embed AI capabilities into customer‑facing products, internal tools, and operational workflows, ensuring solutions integrate naturally and deliver measurable value.
• Build full‑stack systems spanning backend services, APIs, data layers, and frontend interfaces.
• Translate ambiguous business and operational problems into scalable, maintainable, AI‑enabled technical solutions.
• Apply strong systems thinking to ensure reliability, performance, security, permissions, and auditability across platforms.
• Collaborate closely with engineers, teams, and stakeholders across the company to identify high‑impact opportunities and drive adoption.
• Participate in production support and incident response for owned systems, helping define and uphold reliability and operational best practices.
• Mentor AI team members through code reviews, design feedback, and hands‑on guidance, raising the overall quality bar of the team.

What We Look for

• 3–5 years of professional experience in software engineering, AI engineering, platform engineering, or related roles.
• Hands‑on experience designing, building, and shipping AI‑powered systems into production environments.
• Strong proficiency in Python, SQL, and frontend frameworks such as React.
• Proven experience designing and owning production‑grade full‑stack systems.
• Experience working with distributed systems, internal platforms, or complex data workflows.
• Ability to operate effectively in ambiguous problem spaces and drive solutions with minimal direction.

Preferred Qualifications

• Experience building AI‑first platforms or internal products from scratch, including early architectural decisions.
• Strong foundation in core machine learning and data science principles, including supervised/unsupervised learning, feature engineering, model evaluation, and statistical inference.
• Experience with transformer architectures (BERT, GPT, etc.) and understanding of attention mechanisms, tokenization, and fine‑tuning strategies for domain‑specific applications.
• Experience developing AI‑assisted or agentic systems that interact with tools, data, or workflows.
• Familiarity with embeddings and vector representations, including text embeddings, similarity search, and integration with vector databases (Pinecone, Weaviate, pgvector, or similar).
• Experience with NLP techniques including text classification, named entity recognition, semantic search, and information extraction.
• Familiarity with cloud‑native development using AWS.
• Understanding of prompt engineering, retrieval‑augmented generation (RAG), and LLM application patterns.
• Experience with containerized systems and orchestration tools such as Docker and Kubernetes.
• Exposure to CI/CD pipelines and modern development workflows (e.g., GitLab).