Karbon
AI-powered practice management software
AssociateAIEngineer
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“Associate AI Engineer at Karbon. Skills: AI, machine learning, LLMs, Python, ML frameworks, deploying AI/ML solutions. building new capabilities. maintaining and improving existing systems”
What You'll Achieve.
Balance Speed and Quality; producing reliable, maintainable, and well-tested solutions; operational stability; customer impact of their work; creating real efficiencies for our users
Industry & Context.
Sound judgment in making trade-offs between velocity and long-term sustainability; independently translate problems into actionable technical approaches; enhance productivity, problem-solving, and innovation
What They're Looking For.
Must Have
1-3 years of experience developing and deploying AI/ML solutions, Experience working with LLMs (RAG, Chaining, MCP, etc), Proficiency in Python and relevant ML frameworks (Sklearn, Pytorch, Tensorflow, spaCy, etc. ), Good understanding of traditional machine learning techniques (linear/logistic regression, randomForest, GBM, etc. ), Familiarity with machine learning development lifecycles, A Bachelor’s degree in Computer Science, Artificial Intelligence, Statistics, or equivalent experience
Nice to Have
Experience in agentic frameworks (ADK, LangGraph, Agent SDK etc. ), Previous MLOps experience, Experience developing and maintaining data pipelines (Snowflake, DBT, etc), Previous experience in backend software development (in particular C#), Knowledge of deep learning architectures, Experience deploying machine learning models to complex production environments (Previous experience with Azure is advantageous), Masters or PhD advantageous
What You'll Do.
building new capabilities
maintaining and improving existing systems
designing scalable solutions
reducing technical debt
supporting operational stability
contributing to continuous improvement
translating problems into actionable technical approaches
proactively identify improvements
continuously expand relevant technical expertise
accountable for the quality
and customer impact of their work from design through post-release support
follow through on commitments
apply technical fundamentals
embrace AI tools and approaches to enhance productivity
analyse problems and apply machine learning to solve them
develop a wide range of machine learning applications
building end-to-end agentic solutions in our application
Model evaluation and selection
Work with data engineers to build and maintain data pipelines
How You'll Work.
Team & Collaboration
collaborate effectively; contribute constructively in design discussions, reviews, and planning; communicate clearly about progress and risks; support shared team outcomes in both hybrid and distributed environments; Work with data engineers, analysts and full stack developers; collaborative, team-oriented culture
Communication Scope
communicate clearly about progress and risks
Process & Methodology
meeting agreed timelines
Full Job Description
About Karbon Karbon is the global leader in AI-powered practice management software for accounting firms. We provide an award-winning cloud platform that helps tens of thousands of accounting professionals work more efficiently and collaboratively every day. With customers in 40 countries, we have grown into a globally distributed team across the US, Australia, New Zealand, Canada, the United Kingdom, and the Philippines. We are well-funded, ranked #1 on G2, growing rapidly, and have a people-first culture that is recognized with Great Place To Work® certification and on Fortune magazine's Best Small Workplaces™ List. Associate AI Engineer Our Engineering Standards Balance Speed and Quality Engineers are expected to balance delivery speed with a strong commitment to quality, meeting agreed timelines while producing reliable, maintainable, and well-tested solutions. Sound judgment in making trade-offs between velocity and long-term sustainability is essential. Collaborate Effectively Engineering is collaborative by default. Team members are expected to contribute constructively in design discussions, reviews, and planning, communicate clearly about progress and risks, and support shared team outcomes in both hybrid and distributed environments. Build and Maintain Systems Engineers are responsible for building new capabilities while maintaining and improving existing systems. This includes designing scalable solutions, reducing technical debt, supporting operational stability, and contributing to continuous improvement. Operate with Autonomy A high degree of autonomy is expected. Given clear objectives, engineers should independently translate problems into actionable technical approaches, proactively identify improvements, and continuously expand relevant technical expertise. Ownership and Accountability Ownership is fundamental. Engineers are accountable for the quality, performance, and customer impact of their work from design through post-release support, and are
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