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Senior AI Architect

Talent GlideUnited States🇺🇸United StatesPosted 1 Sept 2026

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
United States
Posted
Yesterday
AWSMLOpsMachine LearningAzureBigQueryGenerative AIGoogle CloudKubernetesStakeholder Management

Job Description

Senior AI Architect
Duration: 3–6 Months (Contract-to-Hire)
Location: Remote

Job Overview
Client is seeking a Senior AI Architect to lead the architecture and technical strategy for AI/ML, Generative AI, automation, and agentic AI solutions within the Finance Technology organization.
The ideal candidate will have strong enterprise architecture experience, hands-on knowledge of cloud platforms and AI/ML technologies, and the ability to work with both senior business stakeholders and engineering teams.
Key Responsibilities
  • Define AI/ML architecture strategy, standards, and technology roadmaps.
  • Design scalable architectures for Generative AI, Machine Learning, RAG, and Agentic AI solutions.
  • Develop reusable AI/ML frameworks and platforms for finance use cases such as forecasting, fraud detection, reconciliation, reporting, and analytics.
  • Design RAG, Knowledge Graph, GraphRAG, semantic search, and vector database solutions.
  • Define architectures for multi-agent workflows, orchestration, tool integration, and human-in-the-loop processes.
  • Create detailed architecture designs covering data pipelines, APIs, integrations, model serving, security, and governance.
  • Guide engineering teams through technical design, implementation, and code/design reviews.
  • Ensure AI solutions meet enterprise security, privacy, compliance, governance, and audit requirements.
  • Drive adoption of MLOps/LLMOps practices.
  • Evaluate and recommend cloud platforms, AI tools, frameworks, and technologies.
Required Qualifications
  • 12+ years of experience in Enterprise Architecture, Cloud Architecture, or Distributed Systems.
  • Strong hands-on experience with AI/ML and Generative AI in production environments.
  • Expertise across Azure, AWS, and Google Cloud Platform.
  • Strong experience with Kubernetes and containerized platforms.
  • Experience with event-driven architectures and large-scale data processing.
  • Strong knowledge of LLMs, RAG, prompt engineering, vector databases, semantic search, and Knowledge Graphs.
  • Experience designing Agentic AI / multi-agent workflows.
  • Strong understanding of ML use cases including forecasting, anomaly detection, fraud detection, and predictive analytics.
  • Experience with large-scale data pipelines, APIs, databases, and distributed systems.
  • Experience with Azure OpenAI, Azure ML, Vertex AI, BigQuery ML, or similar AI/ML services.
  • Strong communication, stakeholder management, and technical leadership skills.
Preferred Qualifications
  • Experience in Finance, Banking, FinTech, or other regulated industries.
  • Experience with MLOps/LLMOps and AI governance/model risk frameworks.
  • Relevant cloud or architecture certifications such as Azure, AWS, Google Cloud Platform, or TOGAF

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