Senior AI Engineer

Senior AI Engineer at Karbon Join to apply for the Senior AI Engineer role at Karbon. Karbon is the global leader in practice management software for growth‑minded accounting firms. We provide an award‑winning, highly collaborative cloud platform that streamlines work and communication, enabling the average accounting firm using Karbon to save 18.5 hours per week per employee. We serve customers in 34 countries and operate a globally distributed team based throughout the US, Australia, New Zealand, Canada, the United Kingdom, and the Philippines. We are well‑funded, ranked #1 on G2, have a fantastic team culture built on our values, are growing rapidly, and making a global impact. About this role and the work We are seeking innovative Senior AI & ML engineers who thrive in a fast‑paced environment. You will have the unique opportunity to take on greenfield projects within a supported team, backed by executive‑level investment. Karbon is at the start of its AI journey and you will shape our product and processes. The successful candidate will design, implement, and maintain AI models in a distributed production environment and develop bespoke AI solutions (not just using LLMs) to automate workflows, generate insights, and create efficiencies for our users. Responsibilities Designing AI systems – learn problems and apply machine learning to solve them Machine learning and AI development – develop a wide range of machine learning applications Model evaluation and selection – look beyond basic evaluation metrics and consider wider impacts Productionise AI – own the post‑deployment process by managing production monitoring Data management – work with data engineers to build and maintain data pipelines Collaboration – work in a cross‑functional team with data engineers, analysts, and full‑stack developers About you We look for: 5+ years of experience developing and deploying AI/ML solutions Experience in a tech lead role (architectural decision making, completing tech designs, coaching junior engineers) Strong proficiency in LLM development and previous experience building autonomous agents (ADK, LangGraph, Agents SDK, etc.) Strong proficiency in Python and relevant ML frameworks (Sklearn, Pytorch, Tensorflow, spaCy, etc.) Strong understanding of traditional machine learning techniques (linear/logistic regression, random forest, GBM, etc.) Strong understanding of the machine learning development lifecycle, including MLOps, deployment, and monitoring A bachelor’s degree in Computer Science, Artificial Intelligence, Statistics, or equivalent experience (master’s or PhD advantageous) It would be advantageous if you have: Experience developing and maintaining data pipelines (Snowflake, DBT, etc.) Previous experience in backend software development, particularly C# Previous experience in Azure Why work at Karbon? Gain global experience across the USA, Australia, New Zealand, UK, Canada, and the Philippines 4 weeks annual leave plus 5 extra “Karbon Days” off a year Flexible working environment Work with and learn from an experienced, high‑performing team Be part of a fast‑growing company that promotes high performers from within A collaborative, team‑oriented culture that embraces diversity, invests in development, and provides consistent feedback Generous parental leave Karbon embraces diversity and inclusion. Research has shown that women and underrepresented groups are less likely to apply to jobs unless they meet every single criterion. If you've made it this far in the job description but your past experience doesn't perfectly align, we encourage you to still apply. You could still be the right person for the role We recruit and reward people based on capability and performance. We don’t discriminate based on race, gender, sexual orientation, gender identity or expression, lifestyle, age, educational background, national origin, religion, physical or cognitive ability, and other diversity dimensions that may hinder inclusion in the organization. If there are any adjustments or accommodations that we can make to assist you during the recruitment process, and your journey at Karbon, contact us at for a confidential discussion. At this time, we request that agency referrals are not submitted for this position. We appreciate your understanding and encourage direct applications from interested candidates. Thank you Referrals increase your chances of interviewing at Karbon by 2× #J-18808-Ljbffr