Design, develop, and implement cutting-edge Generative AI solutions for the Finance Smart Assistant, leveraging and enhancing existing frameworks.
Build and refine applications powered by Large Language Models (LLMs) with strong emphasis on prompt engineering, fine‑tuning, and model evaluation.
Lead the integration of Retrieval-Augmented Generation (RAG) to improve the accuracy, reliability, and context‑awareness of AI-driven insights.
Continuously experiment with new architectures, optimization techniques, and model enhancements to advance system capabilities.
Utilize table transformers, Python‑based extractors, and other advanced packages to process complex financial datasets.
Develop robust pipelines for data ingestion, preprocessing, and feature engineering aligned with financial domain requirements.
Own the full lifecycle of GenAI solutions—from concept and prototyping to production deployment and performance monitoring.
Ensure model scalability, reliability, and governance through best practices in ML Ops and responsible AI.
Partner with product managers, data engineers, analysts, and business stakeholders to ensure seamless integration of AI solutions within existing financial workflows.
Translate technical insights into clear, actionable recommendations for both technical and non‑technical audiences.
Stay current with the latest advancements in LLMs, RAG, GenAI frameworks, and AI/ML techniques.
Actively contribute to ongoing innovation initiatives by sharing insights, proposing enhancements, and building proof‑of‑concepts.

Requirements

Strong experience with Generative AI, LLMs, RAG, and modern NLP techniques.
Proficiency in Python and hands-on experience with AI/ML frameworks (HuggingFace, PyTorch, TensorFlow, LangChain, etc.).
Experience with table transformers, document AI, or structured data extraction.
Expertise in prompt engineering, fine-tuning, and model optimization.
Solid understanding of data pipelines, preprocessing methods, and API integration.
Experience deploying AI systems to production (Azure/AWS/GCP preferred).
Ability to communicate complex concepts clearly to diverse audiences.
Background in Finance domain is a plus.

Benefits

Paid time off based on employee grade (A-F)
Vacation: 12-25 days, depending on grade
Company paid holidays
Personal Days
Sick Leave
Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
Life and disability insurance
Employee assistance programs
Other benefits as provided by local policy and eligibility

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills

Generative AILarge Language Modelsprompt engineeringfine-tuningmodel evaluationRetrieval-Augmented Generationdata ingestionfeature engineeringML Opsdocument AI

Soft skills

communicationcollaborationproblem-solvinginnovationtechnical translation