AI Finance Solution Architect

About the role

We are seeking an experienced AI Finance Tech Lead / Solution Architect to lead the architecture, design, and delivery of next-generation AI-powered Finance solutions for enterprise customers. This role serves as the technical leader of the Finance AI team and is responsible for defining end-to-end architecture across data, AI models, applications, integrations, and cloud platforms. The candidate will guide engineering teams, drive architecture decisions, and ensure scalable, secure, and production-ready AI solutions.

Key responsibilities

• Design scalable, secure and production-ready enterprise AI solutions
• Define technical approaches for LLMs, RAG, Agents, APIs and system integrations
• Make key technology and architecture decisions
• Guide engineers through design, development and production deployment
• Ensure solution quality, security, performance, reliability and cost efficiency
• Communicate technical decisions and risks to global stakeholders

About you

• Three to Six (3-6) years of hands-on software engineering or solution architecture experience, including proven technical leadership in delivering production-grade LLM / Generative AI / Agent / RAG solutions
• Strong understanding of LLM capabilities, limitations and architecture patterns, with practical experience in prompt engineering, RAG pipelines, tool calling, agent orchestration and model evaluation
• Proven ability to design scalable, secure and maintainable enterprise AI architectures, covering APIs, data ingestion, vector databases, identity and access management, observability, deployment and integration with existing enterprise systems
• Strong hands-on experience with Python and modern backend development, including REST APIs, asynchronous processing, distributed systems and cloud-native deployment
• Demonstrated experience leading architecture decisions, conducting technical reviews, resolving complex engineering issues and guiding engineers from solution design through production launch and ongoing optimization
• Hands-on experience collaborating with distributed, cross-functional global teams across multiple time zones, including product, engineering, data, security, compliance and business stakeholders
• Fluent business English for technical discussions, architecture documentation, stakeholder communication and global meetings
• Working knowledge of enterprise data privacy, security and responsible-AI requirements, including access control, data isolation, sensitive-data handling and auditability
• Practical working knowledge of Jira and Confluence for technical planning, documentation, delivery tracking and cross-team collaboration