GenAI Engineer

ClifyX, INC

Wilmington, NC, United States

about 1 month ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Job source

www.careerbuilder.com

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Microsoft Azure Batch Processing Program Optimization Cyber Security Continuous Delivery Continuous Integration Extract Transform Load (ETL) Data Security Fraud Prevention and Detection Python (Programming Language)

+19 more

Machine Learning Scrum Methodology Systems Development Life Cycle Tensorflow Privacy Controls Scripting Pytorch Large Language Models Prompt Engineering Deep Learning Generative AI AI Platforms Low Latency Deployment Automation Data Management Machine Learning Operations Software Version Control Data Pipelines Microservices

Job description

Design and develop AI/ML and Generative AI solutions for banking use cases including fraud detection, risk modeling, and customer analytics.

Build, fine-tune, and deploy ML models and LLMs for credit scoring, AML, and automation
Implement RAG-based GenAI applications using internal banking data
Develop scalable data pipelines for training, validation, and real-time inference
Collaborate with risk, compliance, finance, and business teams for AI solutions
Ensure regulatory compliance and AI governance standards
Implement data security, privacy, and access control mechanisms
Integrate AI models into production using APIs and microservices
Apply prompt engineering and model optimization techniques
Monitor model performance, drift detection, and continuous improvement
Develop explainable AI (XAI) for transparent decision-making
Optimize cost, latency, and scalability of AI systems
Troubleshoot AI/ML system issues across data and deployment layers
Write efficient Python code using AI frameworks
Follow MLOps best practices (CI/CD, automated deployment)
Ensure responsible AI practices (bias, fairness, ethics)
Mentor teams and contribute to enterprise AI platforms.

Requirements

Languages: Python AI/ML & GenAI: Machine Learning, Deep Learning, LLMs, Prompt Engineering, Fine-tuning Frameworks: TensorFlow, PyTorch GenAI Tools: LangChain, LlamaIndex Vector DB: Pinecone, FAISS Cloud Technologies: AWS / Azure / GCP Data Pipelines: ETL/ELT, Real-time & Batch Processing Integration: APIs, Microservices Concepts: RAG Architecture, XAI, Model Optimization Methodologies: Agile/Scrum, MLOps (CI/CD, Model Versioning, Deployment) Compliance: Banking regulations (SR 11-7, GDPR), Model Risk Management Soft Skills: Strong communication, stakeholder management, and analytical thinking

Skills: Access Control, Analysis Skills, Application Programming Interface (API), Artificial Intelligence (AI), Automation, Banking Regulations, Banking Services, Best Practices, Communication Skills, Continuous Deployment/Delivery, Continuous Improvement, Continuous Integration, Cost Control, Data Management, Financial Compliance, Identify Issues, Information/Data Security (InfoSec), Maintain Compliance, Mentoring, Microservices, Performance Analysis, Performance Modeling, Privacy Controls, Python Programming/Scripting Language, Regulatory Compliance, Risk, Risk Management, Risk Modeling, Scalable System Development, Systems Scalability, Use Cases