领域AI Azure架构师
Domain AI Azure Architect
DomainAI Azure 架构师
AI 架构师，为技术风险领域打造新产品，将大量使用人工智能
所需技能：精通 LLM、API、人工智能架构和设计专业知识。
ASN - SOC 报告（INV）正确
AI 架构师 – 技术风险（ASN – SOC 报告产品）
在技术和创新的战略投资推动下，客户技术部门专注于通过开发稳健的平台和下一代人工智能驱动的产品来推动增长机会并解决复杂的业务挑战。
作为 AI 架构师，您将领导技术风险（ASN – SOC 报告）内新产品的设计和开发，利用先进的人工智能、大型语言模型（LLMs）和基于 API 的架构。
您将与技术人员、数据专家和业务利益相关者紧密合作，结合深厚的领域专业知识和前沿的人工智能能力，交付可扩展的智能解决方案。此职位让您处于将人工智能集成到企业平台的最前沿，实现更智能的自动化、分析和决策。
机会
为技术风险领域的新产品设计和实现端到端的人工智能架构，重点关注 SOC 报告和智能自动化。
定义和管理人工智能模型、流程和基础设施，确保可扩展性、安全性和符合企业及监管标准。
通过引入 LLM、生成式 AI 和高级分析来推动创新。
主要职责
设计和领导 AI/ML 架构，包括基于 LLM 的解决方案、模型编排和智能工作流
开发整合 LLM、API 和企业系统的可扩展架构
定义提示工程、模型微调、评估和监控的框架
在云环境（Azure、AWS、GCP）中构建端到端的人工智能平台
确保人工智能解决方案符合数据隐私、安全和合规要求（技术风险 / SOC 要求）
与跨职能团队合作，将业务需求转化为人工智能驱动的解决方案
设计以 API 为核心的架构，以在各平台上暴露人工智能功能
领导将结构化和非结构化数据集成到人工智能流程中
建立人工智能治理、可解释性和负责任的人工智能的最佳实践
在解决复杂架构挑战方面提供技术领导力
通过识别在流程中嵌入自动化和智能的机会来支持产品创新
查看英文原文
DomainAI Azure Architect
AI ARCHITECT to Build a new product for tech risk which will heavily use a.i.
Skills required:be LLM, API, A.I architecture and design expertise.
ASN - SOC Reporting (INV) correct
AI Architect – Tech Risk (ASN – SOC Reporting Product)
Fueled by strategic investment in technology and innovation, Client Technology is focused on driving growth opportunities and solving complex business challenges through the development of robust platforms and next-generation, AI-powered products.
As an AI Architect, you will lead the design and development of a new product within Technology Risk (ASN – SOC Reporting), leveraging advanced Artificial Intelligence, Large Language Models (LLMs), and API-driven architectures.
You will work closely with technologists, data specialists, and business stakeholders, combining deep domain expertise with cutting-edge AI capabilities to deliver scalable, intelligent solutions. This role places you at the forefront of integrating AI into enterprise platforms, enabling smarter automation, analytics, and decision-making.
The Opportunity
Design and implement end-to-end AI architecture for a new product within Tech Risk, focused on SOC reporting and intelligent automation.
Define and govern AI models, pipelines, and infrastructure, ensuring scalability, security, and compliance with enterprise and regulatory standards.
Drive innovation by incorporating LLMs, generative AI, and advanced analytics into product capabilities.
Key Responsibilities
Design and lead AI/ML architecture, including LLM-based solutions, model orchestration, and intelligent workflows
Develop scalable architectures integrating LLMs, APIs, and enterprise systems
Define frameworks for prompt engineering, model fine-tuning, evaluation, and monitoring
Architect end-to-end AI platforms across cloud environments (Azure, AWS, GCP)
Ensure AI solutions align with data privacy, security, and compliance (Tech Risk / SOC requirements)
Collaborate with cross-functional teams to translate business requirements into AI-driven solutions
Design API-first architectures to expose AI capabilities across platforms
Lead the integration of structured and unstructured data into AI pipelines
Establish best practices for AI governance, explainability, and responsible AI
Provide technical leadership in resolving complex architecture challenges
Support product innovation by identifying opportunities to embed automation and intelligence into workflows
Skills and Attributes for Success
AI Architecture & Design
Strong expertise in designing enterprise-grade AI solutions, including LLM integration and generative AI applications
Large Language Models (LLMs)
Experience with GPT-like models, prompt engineering, fine-tuning, embeddings, and vector databases
API & Microservices Architecture
Ability to design scalable API-driven ecosystems for AI services integration
Cloud & AI Platforms
Hands-on experience with Azure AI, AWS AI/ML, or GCP AI services
Data & AI Integration
Understanding of data pipelines, data lakes, and structured/unstructured data processing for AI use cases
Responsible AI & Governance
Knowledge of AI ethics, bias mitigation, model explainability, and compliance standards
Solution Architecture
Ability to design end-to-end enterprise solutions including security, scalability, and performance considerations
To Qualify for the Role, You Must Have
Strong experience in AI/ML architecture and solution design
Proven experience working with LLMs, generative AI, and AI platforms
Experience designing and integrating APIs and microservices
Cloud experience: Azure (preferred), AWS, or GCP
Familiarity with vector databases, embeddings, and semantic search
Understanding of Tech Risk, compliance, or SOC-related processes (preferred)
Experience in distributed systems and scalable architectures
Education
M.S. or B.S. in Computer Science, Artificial Intelligence, Data Science, Engineering, or related field
What We Look For
Strong analytical and problem-solving skills
Innovative mindset with passion for AI and emerging technologies
Ability to lead architecture decisions and influence stakeholders
Excellent communication and collaboration skills
Ownership mindset and ability to drive initiatives independently
High attention to detail and commitment to quality
remote
advanced english
Originally posted on Himalayas