↳Bachelor's or master's degree in Data Science, Computer Science, AI/ML, Software Engineering, Quantitative Finance, or a related field
↳2-6 years of software engineering experience, including financial services exposure and strong understanding of markets
↳2-6 years delivering ML/AI solutions to production, including end-to-end delivery of LLM-enabled applications (from prototyping to deployment and monitoring)
↳Hands-on experience building and operating RAG applications in production within enterprise-ready environments — including security, access control, observability, evaluation, and cost governance
↳Practical experience deploying open-source models to production
↳Demonstrated experience fine-tuning open-source models (e.g., LoRA/PEFT, instruction tuning, dataset curation, and evaluation of fine-tuned checkpoints against baselines)
↳Strong Python skills and proven ability to design and build maintainable, high-quality software in enterprise environments
↳Working knowledge of the software development lifecycle (SDLC), version control, and modern DevOps practices
↳Demonstrated ability to translate ambiguous business needs into clear scopes, roadmaps, and measurable success metrics
