About the role
Job Description: GenAI Architect – Banking
Experience: 10+ years in software engineering or architecture, with hands-on experience delivering Generative AI solutions Domain: Banking and Financial Services
Role Overview
We are seeking a GenAI Architect to design and implement secure, scalable Generative AI solutions for banking. The role combines enterprise architecture, hands-on AI expertise, and banking domain knowledge to deliver solutions across customer service, operations, risk, and compliance.
Key Responsibilities
- Define the GenAI architecture and roadmap in collaboration with banking business and technology teams. - Design solutions for use cases such as customer and employee assistants, credit document analysis, KYC support, regulatory knowledge retrieval, and operations automation. - Build retrieval-augmented generation (RAG) architectures using banking policies, product documents, procedures, and approved knowledge sources. - Evaluate LLMs, embedding models, vector databases, and orchestration frameworks against accuracy, security, latency, and cost requirements. - Integrate GenAI applications with core banking systems, CRM platforms, document repositories, and enterprise APIs. - Design agentic workflows with controlled tool access, human approvals, and auditable actions. - Implement controls for sensitive customer data, access permissions, data retention, and data residency. - Address risks including hallucinations, prompt injection, data leakage, and inappropriate model outputs. - Establish evaluation, monitoring, versioning, and deployment practices for production AI applications. - Collaborate with information security, compliance, legal, and model risk teams to meet applicable regulatory requirements and internal policies. - Lead architecture reviews, mentor engineers, and guide solutions from proof of concept to production.
Required Skills and Qualifications
- Bachelor’s or master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience. - Strong experience in enterprise architecture and application delivery within banking or financial services. - Hands-on experience developing and deploying production LLM applications. - Proficiency in Python, API development, microservices, and distributed systems. - Strong understanding of RAG, embeddings, semantic search, reranking, prompt engineering, and model evaluation. - Experience with at least one major cloud AI platform, such as Azure OpenAI, Amazon Bedrock, or Google Vertex AI. - Experience with vector databases or vector-enabled search platforms. - Knowledge of banking processes such as retail or corporate banking, lending, payments, KYC/AML, or risk management. - Understanding of secure development, encryption, identity and access management, and audit logging. - Experience with CI/CD, containers, infrastructure as code, and LLMOps. - Strong communication skills and the ability to explain architectural decisions to technical and business stakeholders.
Preferred Qualifications
- Experience navigating model risk reviews and AI governance processes in a bank. - Familiarity with private networking, hybrid deployments, and restricted data environments. - Experience with model fine-tuning, open-weight models, or multimodal document processing. - Experience designing human review and escalation mechanisms for sensitive banking workflows. - Relevant cloud architecture or AI certifications.
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