Jobs via Dice
Gen AI Solution Architect - Onsite
6 Month Contract
Naperville, IL, USA
Role Overview We are seeking an experienced AI / Generative AI Solution Architect to lead the design and implementation of cutting‑edge AI solutions within the banking domain. The ideal candidate will have deep expertise in SaaS‑based AI platforms, cloud‑native architectures, and hands‑on experience in developing and deploying AI/Gen AI models that drive innovation in customer experience, operational efficiency, and risk management.
Key Responsibilities
Define and design scalable AI/Gen AI architectures for banking applications, including conversational AI, predictive analytics, fraud detection, and personalized financial services.
Create detailed architecture diagrams and documentation using tools like iServer or similar.
Develop reference architectures and best practices for integrating AI solutions into core banking systems and digital channels.
Lead the development and deployment of AI/Gen AI models (e.g., LLMs, NLP, RAG solution, Agentic AI Solution) tailored for banking use cases.
Collaborate with data scientists, other architecture domains (Enterprise, Security) and stakeholders to optimize model performance and ensure compliance with regulatory standards.
Architect solutions leveraging SaaS‑based AI platforms and cloud services (AWS, Azure, Google Cloud Platform) for scalability and security.
Ensure seamless integration with existing banking systems and APIs.
Implement AI governance frameworks addressing ethical AI, data privacy, and regulatory compliance (e.g., GDPR, FFIEC).
Secure TDRC and ARB approvals for all solution designs and deployments.
Partner with business leaders to identify AI opportunities and translate them into technical solutions.
Provide thought leadership and technical guidance to cross‑functional teams.
Stay ahead of emerging AI/Gen AI trends and evaluate new technologies for banking applications.
Drive the AI strategy and roadmap aligned with business objectives.
Required Qualifications
Education:
Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or related field.
Experience:
8+ years in solution architecture with at least 3+ years focused on AI/ML and Generative AI, proven experience in designing and deploying SaaS‑based AI solutions in enterprise environments, experience benchmarking multiple SaaS AI solutions/Gen AI Models, hands‑on experience developing AI/Gen AI models including LLMs and RAG solution frameworks.
Technical Skills:
Expertise in AI/ML frameworks (TensorFlow, PyTorch, Hugging Face, RAG solutions, Bedrock, Gen AI Models), strong knowledge of cloud platforms (AWS, Azure, Google Cloud Platform) and SaaS AI offerings, proficiency in API design, microservices, and containerization (Docker, Kubernetes), familiarity with iServer or similar enterprise architecture tools, prior experience building data architecture for data lake and data pipelines at scale.
Domain Knowledge:
Deep understanding of banking processes, regulatory requirements, and security standards.
Soft Skills:
Excellent communication and stakeholder management skills, ability to translate complex technical concepts into business value.
Preferred Qualifications
Experience with AI governance frameworks and ethical AI practices.
Familiarity with financial risk modeling, fraud detection, and customer personalization.
Certifications in AI/ML or cloud architecture (AWS Certified Solutions Architect, Azure AI Engineer, etc.).
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Naperville, IL, USA
Role Overview We are seeking an experienced AI / Generative AI Solution Architect to lead the design and implementation of cutting‑edge AI solutions within the banking domain. The ideal candidate will have deep expertise in SaaS‑based AI platforms, cloud‑native architectures, and hands‑on experience in developing and deploying AI/Gen AI models that drive innovation in customer experience, operational efficiency, and risk management.
Key Responsibilities
Define and design scalable AI/Gen AI architectures for banking applications, including conversational AI, predictive analytics, fraud detection, and personalized financial services.
Create detailed architecture diagrams and documentation using tools like iServer or similar.
Develop reference architectures and best practices for integrating AI solutions into core banking systems and digital channels.
Lead the development and deployment of AI/Gen AI models (e.g., LLMs, NLP, RAG solution, Agentic AI Solution) tailored for banking use cases.
Collaborate with data scientists, other architecture domains (Enterprise, Security) and stakeholders to optimize model performance and ensure compliance with regulatory standards.
Architect solutions leveraging SaaS‑based AI platforms and cloud services (AWS, Azure, Google Cloud Platform) for scalability and security.
Ensure seamless integration with existing banking systems and APIs.
Implement AI governance frameworks addressing ethical AI, data privacy, and regulatory compliance (e.g., GDPR, FFIEC).
Secure TDRC and ARB approvals for all solution designs and deployments.
Partner with business leaders to identify AI opportunities and translate them into technical solutions.
Provide thought leadership and technical guidance to cross‑functional teams.
Stay ahead of emerging AI/Gen AI trends and evaluate new technologies for banking applications.
Drive the AI strategy and roadmap aligned with business objectives.
Required Qualifications
Education:
Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or related field.
Experience:
8+ years in solution architecture with at least 3+ years focused on AI/ML and Generative AI, proven experience in designing and deploying SaaS‑based AI solutions in enterprise environments, experience benchmarking multiple SaaS AI solutions/Gen AI Models, hands‑on experience developing AI/Gen AI models including LLMs and RAG solution frameworks.
Technical Skills:
Expertise in AI/ML frameworks (TensorFlow, PyTorch, Hugging Face, RAG solutions, Bedrock, Gen AI Models), strong knowledge of cloud platforms (AWS, Azure, Google Cloud Platform) and SaaS AI offerings, proficiency in API design, microservices, and containerization (Docker, Kubernetes), familiarity with iServer or similar enterprise architecture tools, prior experience building data architecture for data lake and data pipelines at scale.
Domain Knowledge:
Deep understanding of banking processes, regulatory requirements, and security standards.
Soft Skills:
Excellent communication and stakeholder management skills, ability to translate complex technical concepts into business value.
Preferred Qualifications
Experience with AI governance frameworks and ethical AI practices.
Familiarity with financial risk modeling, fraud detection, and customer personalization.
Certifications in AI/ML or cloud architecture (AWS Certified Solutions Architect, Azure AI Engineer, etc.).
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