AI Specialist - Gen AI NLP BankingFinancial Services

The role:

SoFis AI Specialist GenAI NLP (Banking/Financial Services) is a critical handson engineer position in SoFis growing independent risk organization focussed on applying data processing/reporting and practical artificial intelligence techniques to solve real world problems. This role will be instrumental in conceptualizing prototyping and implementing bestinclass AIbased solutions to meet risk management requirements.

This handson individual contributor role will work closely with the Director of Risk Analytics and will play a pivotal role in developing data reporting and infrastructure solutions supporting the risk function. This is a crucial role for the independent risk function as we execute our mission to help more members get their money right.

What youll do:

• AI Solution Development: Design and develop AIbased solutions leveraging available Generative AI (Gen AI) LLMs natural language processing and other transformer models as applicable to enable enhanced risk reporting conversational risk analysis/commentary and automated risk management processes.
• Data Handling and Preprocessing: Work with large structured/unstructured data sets performing data sourcing preprocessing tokenization and feature extraction to prepare data for Gen AI adoption.
• Model Adoption: Design develop and optimize RAG (RetrievalAugmented Generation) on available LLMs integrated with vector databases to develop solutions for specific use cases to optimize output accuracy and effectiveness ensuring enhanced user experiences.
• Cross Functional Collaboration: Coordinate with crossfunctional teams to distill specific requirements project roadmaps and ensure accurate and ontime project deliveries
• Solution Performance Monitoring: Periodically assess solution performance ensuring they meet applicable performance compliance and security standards. Implement retraining and continuous improvement strategies.
• Proof of Concepts & Proposals Identify areas for process enhancements and automation to streamline workflows and increase productivity within the risk management function.
• AI Innovation: Stay uptodate with the latest trends and advancements in GenAI LLMs and NLP evaluating and experimenting with new techniques and tools to push the boundaries of AI innovation in the banking sector.

What youll need:

• Bachelors or Masters degree in Computer Science Data Science AI Machine Learning or a related field. PhD is a plus.
• 5 years software development experience with 3 years of handson experience in AI/ML with a focus on Generative AI Large Language Models and NLP preferably in the banking or financial services domain.
• Proven experience in developing and deploying productiongrade GenAI and NLP solutions for risk management document understanding fraud detection or compliance.
• Programming Languages: Proficiency in Python is required; Rust is a plus
• LLM/GenAI Technologies: Export experience with frameworks like OpenAI GPT GPT3 GPT4 Codex or similar LLM platforms (e.g. Googles PaLM Metas LLaMA Anthropics Claude or custom finetuning on Hugging Face).
• NLP Libraries: Proficiency in NLP libraries such as Hugging Face Transformers SpaCy NLTK Tensorflow Torch and OpenNLP.
• Data Engineering: Experience with largescale data handling including unstructured and structured data pipelines.
• Cloud Platforms: Experience with cloudbased machine learning and AI platforms such as AWS (SageMaker Bedrock) and Snowflake with a focus on GenAI model training deployment and monitoring.
• MLOps and Deployment: Handson experience in deploying machine learning models using CI/CD pipelines containers (Docker Kubernetes) and APIs for serving LLM/NLP models at scale.
• APIs & Microservices: Experience developing and integrating AIpowered APIs and microservices architecture into banking applications.
• Data Storage: Experience with relational and NoSQL databases (e.g. PostgreSQL Snowflake) and data lakes for handling large amounts of text data.
• Search and Retrieval: Experience with vector databases and retrievalaugmented generation (RAG) techniques using systems like Elasticsearch Pinecone or FAISS for enhancing LLM performance.
• Strong analytical and problemsolving skills with attention to detail and an ability to work with complex largescale systems.
• Ability to communicate complex AI concepts and solutions clearly to nontechnical stakeholders.
• Strong collaboration skills with experience working in agile crossfunctional teams.
• Experience in banking or financial services use cases such as conversational AI for customer service intelligent document processing for loan applications fraud detection or risk analysis.

Nice to have:

• Familiarity with regulatory frameworks and ethical considerations in AI within the banking industry (e.g. GDPR data privacy model explainability).

Required Experience:

Unclear Seniority