AI Software Engineer

Role overview An AI Software Engineer is needed to design, build, and deploy artificial intelligence solutions that power enterprise financial operations inside a leading ERP platform. The role sits within a fast-paced, innovation-driven engineering team and focuses on creating scalable, production-ready AI systems that automate workflows and deliver measurable business value. It suits a technically curious problem-solver who thrives at the intersection of AI research, software craftsmanship, and product impact.

Responsibilities - Design, prototype, and ship AI systems for real-world business applications spanning the full financial lifecycle. - Build and maintain end-to-end machine learning pipelines that support key product features. - Collaborate with product managers, data scientists, and engineers to deliver integrated, user-facing AI capabilities. - Write clean, well-documented code in Python, JavaScript, or statically typed languages for both backend and frontend integration. - Evaluate AI frameworks, tools, and cloud infrastructure, then optimize deployed models for performance, scalability, and reliability. - Lead experimentation efforts, mentor junior engineers, and communicate findings clearly to technical and non-technical audiences.

Requirements - Two or more years of software engineering experience focused on AI or machine learning applications. - Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a closely related field; a Master's degree is preferred. - Hands-on experience with large language models, agent frameworks such as LangGraph, AutoGen, or DSPy, and production AI deployments. - Strong proficiency in Python plus working familiarity with JavaScript or statically typed languages. - Solid understanding of both relational databases (SQL) and non-relational databases, plus familiarity with AWS or Azure. - Strong analytical, problem-solving, and communication skills in English, with a commitment to ethical AI practices.

Nice to have - Containerization experience for AI workloads. - Exposure to financial operations, ERP systems, or SaaS product environments.

Benefits and work setup - Fully remote, globally distributed team built around autonomy and high-trust flexibility rather than micromanagement. - High-velocity SaaS culture that encourages self-directed professional growth and ownership of outcomes. - Equal opportunity employer committed to a diverse, equitable, and inclusive workplace. - Employment structure varies by jurisdiction: at-will in the United States and fixed-term or permanent contracts elsewhere, governed by local statutory requirements.