GenAI Architect - Banking

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.