• ICapital is seeking an Associate AI Engineer to help build and scale production-grade AI systems that deliver real business outcomes • This individual will be on the AI/ML team and will work closely with senior AI and machine learning engineers, as well as cross-functional partners, to design, implement, evaluate, and operate AI capabilities as APIs and services in a real-world FinTech environment • Design and implement modular AI capabilities including LLM-based reasoning, document intelligence (OCR/IDP), intelligent knowledge systems, and agentic orchestration to power internal and external workflow automation • Own components of the full AI system life cycle to achieve tangible business outcomes, including scoping, POC, solution design, model development, deployment, monitoring and continuous improvement in production environments • Build robust evaluation pipelines for AI systems, defining statistically sound, problem-specific metrics, constructing and curating benchmark datasets, and enforcing strict dataset and model versioning to ensure reproducibility and continuous improvement • Collaborate across teams and communicate results clearly via documentation, write-ups, and handoffs Benefits • Employer-matched retirement plan; • Generous unlimited paid-time off (PTO) and parental leave (benefits vary by country and not all benefits are offered in every location) • Generously subsidised health care with 100% employer-paid dental, vision, telemedicine, and virtual mental health counselling- This role is ideal for an engineer early in their career who enjoys turning ambiguous problem statements into working systems, and who pairs creative problem-solving with disciplined measurement, reproducibility, and operational rigor • This individual will be expected to bring strong analytical fundamentals, curiosity, and a bias toward delivering robust, maintainable systems • Experience with various agentic communication protocols, (i.e. MCP, A2A) is a plus • Familiar with software development best practices (source control, CI/CD, testing, documentation) and working through a full development lifecycle • Strong proficiency in Python • Solid fundamentals in statistics, exploratory data analysis, and the ability to reason about data quality, experiments, and error patterns • 2-3 years of relevant experience, including hands-on experience developing production AI/ML systems, including exposure to AWS or cloud-native development patterns for AI/ML workloads, and familiarity with AI development life cycle best practices • Experience with modern LLM tooling (i.e. transformers, unsloth, vLLM, agentic frameworks) or document AI approaches (IDP) • Clear written and verbal communication with the ability to document work and collaborate in a team setting