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SNI Technology

AI Engineer- Multimodal Models & Regulatory Intelligence

SNI Technology, Soperton, Georgia, United States, 30457

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We are seeking an accomplished

Artificial Intelligence (AI) Engineer

with expertise in

multimodal model development , particularly as it relates to extracting insights from

regulatory, legal, and financial datasets , including those from the

SEC and global regulatory bodies . In this role, you'll design and deploy intelligent systems that combine natural language, structured financial data, and other modalities to power research, compliance, and investment decision-making within the Web3 ecosystem. This is a high-impact opportunity at the intersection of

AI, regulation, and decentralized technologies , where your work will support internal intelligence efforts and empower portfolio companies navigating evolving global regulatory landscapes. What You’ll Do Design, train, and optimize multimodal AI models that integrate unstructured legal texts (e.g., SEC filings, enforcement actions), structured financial data, and other modalities (e.g., tabular, visual, audio). Build systems for automated understanding, summarization, and extraction of relevant information from complex regulatory and legal documents. Support internal risk assessment, compliance tooling, and regulatory strategy through the application of AI to public filings, global regulatory frameworks, and historical precedents. Collaborate with internal teams and portfolio companies to deploy regulatory-aware AI solutions that assist with governance, transparency, and responsible innovation. Evaluate and apply emerging AI techniques (e.g., retrieval-augmented generation, LLMs, graph-based reasoning) to continuously improve model relevance and accuracy. Contribute to internal and external thought leadership at the intersection of AI, regulation, and decentralized systems. Who You Are

4–6+ years of experience in AI/ML, with demonstrated success developing multimodal or NLP-driven systems focused on legal, regulatory, or financial domains. Proficiency in PyTorch, Hugging Face Transformers, LangChain, or equivalent frameworks for building and serving AI models. Deep familiarity with SEC filings, global regulatory bodies (e.g., FCA, ESMA, MAS), and structured datasets (e.g., EDGAR, XBRL, SEDAR). Strong understanding of model training pipelines, including data annotation, fine-tuning, and evaluation in real-world regulatory use cases. Comfortable navigating ambiguity and working independently on research-heavy, experimental initiatives. Bonus: Experience working in or adjacent to crypto, fintech, or compliance tech. Bonus: Contributions to AI research, regulatory technology (RegTech), or open-source initiatives.

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