• 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.

• The AI Engineer is responsible for building, deploying, and operating production-grade AI and Agentic AI solutions across the enterprise. • This is a hands-on engineering role focused on implementing LLM-powered applications, orchestration and multi-agent workflows, and secure API-driven integrations using Azure AI Foundry and Azure-native services. • The role works across the full AI lifecycle —from system design and development to production operations—ensuring solutions are secure, scalable, observable, and governed. • The AI Engineer partners closely with Engineering Leads, architects, data science teams, and platform/security stakeholders to translate AI use cases into reliable, enterprise ready systems.

The salary range for this role is $50,000 - $120,000 per year (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. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping! About the Role: We are seeking a talented and motivated Sr. AI engineer who is best in class with a high IQ plus a high EQ. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with abundant prospects for career advancement. You will be responsible for overseeing the design, development, and deployment of machine learning models that power and enhance our financial platform. In this role, you will drive the creation of scalable machine learning solutions for personalized recommendations in the Sezzle marketplace, fraud detection, and credit risk assessment, utilizing a combination of cloud services, open-source tools, and proprietary algorithms. Your leadership will be key in blending machine learning development and operations (MLOps) to automate and optimize the full lifecycle of our ML models. You will collaborate with a team of engineers and data scientists to build large-scale, high-quality solutions that address diverse challenges in the shopping and fintech space. You’ll ensure our AI-driven features are robust, efficient, and scalable as we continue to grow. What You'll Do: - Design, Build, and Maintain Scalable ML Infrastructure: Lead the design and development of scalable machine learning infrastructure on AWS, utilizing services like AWS Sagemaker for efficient model training and deployment. - Collaborate with Product Teams: Work closely with product teams to develop MVPs for AI-driven features, ensuring quick iterations and market testing to refine solutions effectively. - Develop Monitoring & Alerting Frameworks: Create and enhance monitoring and alerting systems for machine learning models to ensure high performance, reliability, and minimal downtime. - Support Marketing Team’s AI Utilization with an eye on Cross-Departmental impact: Enable various departments within the organization to leverage AI/ML models, including cutting-edge Generative AI solutions, for different use cases. - Provide Production Support: Offer expertise in debugging and resolving issues related to machine learning models in production, participating in on-call rotations for operational troubleshooting and incident resolution. - Scale ML Architecture: Design and scale machine learning architecture to support rapid user growth, leveraging deep knowledge of AWS and ML best practices to ensure robustness and efficiency. - Mentor and Elevate Team Skills: Conduct code reviews, mentor team members, and elevate overall team capabilities through knowledge sharing and collaboration. - Stay Ahead of the Curve: Stay updated with the latest advancements in machine learning technologies and AWS services, driving the adoption of cutting-edge solutions to maintain a competitive edge. What We Look For: - Bachelor's degree in Computer Science, Computer Engineering, Machine Learning, Statistics, Physics, or a relevant technical field, or equivalent practical experience. - At least 6+ years of experience in machine learning engineering, with demonstrated success in deploying scalable ML models in a production environment. Preferred Qualifications: - Deep expertise in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related technical fields. - Proven track record of developing machine learning models from inception to business impact, demonstrating the ability to solve complex challenges with innovative solutions. - Proficiency with Python is required, and experience with Golang is a plus. - Demonstrated technical leadership in guiding teams, owning end-to-end projects, and setting the technical direction to achieve project goals efficiently. - Experience working with relational databases, data warehouses, and using SQL to explore them. - Strong familiarity with AWS cloud services, especially in deploying and managing machine learning solutions and scaling them in a cost-effective manner. - Knowledgeable in Kubernetes, Docker, and CI/CD pipelines for efficient deployment and management of ML models. - Comfortable with monitoring and observability tools tailored for machine learning models (e.g., Prometheus, Grafana, AWS CloudWatch) and experienced in developing recommender systems or enhancing user experiences through personalized recommendations. - Solid foundation in data processing and pipeline frameworks (e.g., Apache Spark, Kafka) for handling real-time data streams. About You: - You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed. - You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things - You need action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking. - You earn trust - you listen attentively, speak candidly, and treat others respectfully. - You have backbone; disagree, then commit - you can respectfully challenge decisions when you disagree, even when doing so is uncomfortable or exhausting. You have conviction and are tenacious. You do not compromise for the sake of social cohesion. Once a decision is determined, you commit wholly. - You deliver results - you focus on the key inputs and deliver them with the right quality and in a timely fashion. Despite setbacks, you rise to the occasion and never settle. What Makes Working at Sezzle Awesome: At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators. We believe in surrounding ourselves with only the best and the brightest individuals. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire. #Li-remote #full-time

This is Engineering at Lattice At Lattice, we build software that helps people and organizations thrive. Our AI Engineering team defines how intelligence works across our platform - how AI systems are measured, improved, and trusted in production. This Staff-level role shapes the foundations that determine AI quality, reliability, and impact at scale. What You Will Do You will architect and scale the infrastructure that powers AI quality, reliability, and reuse across Lattice. AI Evaluation & Quality - Design and scale an end-to-end AI evaluation framework spanning offline evals, production tracing, and human feedback loops. - Define meaningful performance metrics (task completion, hallucination, response quality, engagement, business impact) and build the datasets and automated scoring systems that prevent regressions. - Identify and quantify the drivers of agent quality improvement and set methodological standards for evaluation across the organization. Agent Architecture & Production Systems - Architect reusable agent infrastructure (multi-turn workflows, LLM DAGs, recommendation systems, standardized topologies) using LangGraph or comparable frameworks. - Build and scale RAG pipelines, vector retrieval systems, and production-grade AI infrastructure with strong reliability, observability, and performance. - Make principled build-vs-buy decisions across LLM providers, agent frameworks, and evaluation tooling, balancing capability, cost, latency, and risk. - Engineer AI systems as reusable internal platforms that multiply product engineering velocity at Lattice. Technical Leadership - Own projects end-to-end: scope, design, execution, and delivery. - Set technical direction for agent quality and evaluation strategy across Lattice engineering teams. - Lead rigorous discussions on AI system design and evaluation methodology. - Raise the AI engineering bar through mentorship, code review, and clear technical communication across engineering and leadership. What You Will Bring to the Table Experience - 8+ years of professional experience writing and maintaining production-level code, with 5+ years in designing, delivering, and operating AI/ML systems in production. - Deep production experience with LLM systems (prompting, RAG, agent orchestration, evaluation frameworks, fine-tuning). - Experience building and operating agentic systems (multi-step workflows, multi-agent topologies) and managing their failure modes. - Strong command of AI evaluation methodology and statistical experimentation. - Strong system design judgment across scalability, latency, accuracy, reliability, and cost. Technical Skills - Production-grade Python (clean, maintainable, testable systems). - Experience with LangGraph (or comparable agent orchestration frameworks) and LLM observability/evaluation tooling (e.g., LangSmith). - Vector databases and retrieval system design (Pinecone or similar). - Experience operating AI systems in AWS or comparable cloud environments, including CI/CD, monitoring, and deployment workflows. - Familiarity with TypeScript is a plus. - Actively engaged in AI research and industry trends. Nice to Have - Experience with RLHF, LoRA, or other model adaptation techniques. - Background in traditional ML and judgment in selecting ML vs. LLM approaches. - Experience with MLOps tooling (MLflow, DataDog). - Published research, talks, or open-source contributions in AI/ML. - Experience in HR tech or other trust-sensitive domains. Location Requirement: This role is open to candidates located in British Columbia or Ontario, Canada. At this time, we are only able to hire employees residing in these provinces. The estimated annual cash salary for this role is CAD $146,250 - CAD $195,000. This position is also eligible for incentive stock options, subject to the terms of Lattice’s applicable plans. Benefits: The Company offers the following benefits for this position, subject to applicable eligibility requirements: Medical insurance; Dental insurance; Life, AD&D, and Disability Insurance; Natural Disaster Support Program; Wellness Apps; Paid Parental Leave, Paid Time off inclusive of holidays and sick time; Working Remotely Stipend; One time WFH Office Set-Up Stipend; Retirement Plan; Financial Planning; and Learning & Development Budget. Note on Pay Transparency: Lattice provides an estimate of the compensation for roles that may be hired as required by regulations. Compensation may vary based on (a) location, as Lattice factors in specific location when benchmarking compensation for most roles; (b) individual candidate skills and qualifications; and (c) individual candidate experience. Additionally, Lattice leverages current market data to determine compensation, so posted compensation figures are subject to change as new market data becomes available. The salary, other compensation, and benefits information is accurate as of the date of this posting. Lattice reserves the right to modify this information at any time, subject to applicable law. Lattice welcomes and encourages applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the recruitment and selection process. #LI-Remote About Lattice Lattice is on a mission to build cultures where employees and their companies thrive. In an age where employees have more choices than ever before, businesses that put employees first are winning 🏅– and Lattice is building the tools to empower those people-centric companies. Lattice is a people success platform that offers performance reviews, employee engagement surveys, real-time feedback, weekly check-ins, goal setting, and career planning in a way that allows companies to focus on employee development, growth, and engagement – yielding stronger employee retention, performance, and impact to the bottom line 📈. Since launching in 2016, we have grown to over 5,000+ customers globally, including brands like Loom, Robinhood, and Gusto. Lattice is committed to equal treatment and opportunity in all aspects of recruitment, selection, and employment without regard to gender, race, religion, national origin, ethnicity, disability, gender identity/expression, sexual orientation, veteran or military status, or any other category protected under the law. Lattice is an equal opportunity employer; committed to a community of inclusion, and an environment free from discrimination, harassment, and retaliation. By clicking the "Submit Application" button below, you consent to Lattice processing your personal information for the purpose of assessing your candidacy for this position in accordance with Lattice's Job Applicant Privacy Policy.