Senior AI/ML Architect

Required Skills & Experience

-12+ years of progressive experience in enterprise architecture, cloud architecture, and distributed systems/platform solutions. -Proven hands-on experience across major cloud platforms - Azure, GCP, and AWS. -Deep experience with Kubernetes and container-based platform architecture. -Strong background in event-driven architectures/frameworks and high-volume, high-throughput data processing systems. -Demonstrated experience architecting GenAI and Machine Learning solutions in production environments. -Experience in financial data processing and analytics, ideally within a finance, banking, or FinTech IT organization. -Track record architecting AI/ML foundational frameworks/platforms used across multiple teams or use cases.

Nice to Have Skills & Experience

-Prior experience within a Finance Technology, Banking, or regulated financial services environment. -Experience with MLOps/LLMOps tooling and model governance/risk frameworks. -Relevant cloud or architecture certifications (Azure Solutions Architect, GCP Professional Cloud Architect, AWS Solutions Architect, TOGAF, etc.).

Job Description

We are looking for a Senior AI Architect who will serve as the top AI/ML technical authority for the finance IT organization - someone who can translate a business transformation vision into a coherent AI/ML technical strategy, design the end-to-end architecture that makes that strategy real, and guide engineering teams through detailed design and implementation. This is a highly senior, hands-on architecture role. You will operate at multiple altitudes: shaping multi-year AI/ML roadmaps with business and technology leaders, producing detailed reference architectures and design standards, and working directly with engineers to solve hard design problems. You will be the primary architectural voice for GenAI, machine learning, automation, and agentic systems across finance technology.

-You will be responsible for but not limited to:

Define the AI/ML technical strategy that underpins the finance organization's broader business transformation vision. -Establish and evangelize an “AI-first” architectural philosophy across finance technology - identifying where GenAI, ML, and automation should be embedded by design rather than bolted on. -Architect AI/ML foundational frameworks and platforms that can be reused across multiple finance use cases (fraud detection, forecasting, reconciliation, reporting, analytics, Intelligent document/content/Audio Processing and beyond). -Design high-performing, complex semantic layers using advanced techniques such as RAG, Knowledge Graphs, and GraphRAG, enabling natural language query against large, complex financial databases with extensive table relationships