Technology Architect Azure platform Job at IQZ Systems

Experience Technology Architect

Location

Japan , Tokyo

Salary:

Not provided

AKQA

Expiration Date

Until further notice

Requirements

Bachelorʼs degree in Computer Science, IT, or related field
5+ years of experience in software development or system Implementation
3+ years of experience delivering customer-facing services on the vendor side
Understanding in frontend frameworks like ReactJS and backend technologies or equivalent technologies
Understanding of modern cloud infrastructure such as Vercel or Netlify, and major cloud providers like GCP, AWS or Azure
Having an interest in advanced technology solutions and being proactive in acquiring new skills
A person who can be an advocate for global standard framework and development methodologies

Job Responsibility

Facing Japanese customers and collaborating with global team on activities related to the technical aspects of the project
Understanding proposed customer experiences and interpreting and document technical requirements
Define technology requirements and propose solutions based on company best practice
Platform Evaluation and selection to meet client requirements
Research best practices and proactively getting help of local and global colleagues to shape technical solutions
Support the design and implementation of frontend and backend architecture to drive customer experiences
Research and ensure best practices in accessibility, performance, and security
Evaluate existing client architectures and suggest appropriate improvements to meet their goals
Recruit and oversee technology development teams

Fulltime

Senior AI Platform Architect

As an AI Platform Architect II at Teradyne, you will be a pivotal leader at the ...

Location

United States , North Reading

Salary:

139900.00 - 223900.00 USD / Year

Teradyne

Expiration Date

Until further notice

Requirements

6-8 years in Information Technology including Enterprise Architecture and AI/ML/GenAI Engineering. Proven experience in designing and implementing large-scale, enterprise-wide AI solutions.
Bachelor's Degree in Computer Science, Information Systems, Engineering, or a related field required
Deep understanding of AI and machine learning concepts, including generative AI, large language models (LLMs), and MLOps.
Expertise in designing and building solutions on cloud platforms, with a strong preference for Microsoft Azure and a working knowledge of Google Cloud Platform.
Hands-on experience with and a deep architectural understanding of our core AI and data platforms: Microsoft 365 Copilot, Microsoft Copilot Studio, Azure AI (including the future Azure AI Foundry), Google Vertex AI, and Snowflake Cortex AI.
Strong knowledge of data architecture, data governance, and data security best practices.
Familiarity with Infrastructure as Code (IaC) and CI/CD principles.
Exceptional leadership and communication skills, with the ability to articulate a clear vision and influence stakeholders at all levels of the organization.
Analytical mindset with a focus on delivering measurable business outcomes.
Strong strategic thinking and business acumen, with the ability to connect technology solutions to business value.

Job Responsibility

Design and evangelize a cohesive, enterprise-wide AI and Data architecture.
Create the blueprint for a scalable and secure ecosystem that leverages investments in Microsoft 365 & Copilot, Azure Foundry, Google Vertex AI, and Snowflake Cortex AI.
Guide the selection of AI tools, define the data integration strategy, and establish reusable patterns for agentic development.
Be a key change agent, responsible for embedding AI into the fabric of the business
Bridge the gap between strategy and execution by fostering an AI-ready culture, building institutional literacy.
Architect and operationalize the enterprise AI strategy by developing a comprehensive architectural blueprint and component-level roadmap.
Lead the design of a unified AI ecosystem that integrates our core platforms.
Establish and champion architectural standards, reusable MLOps & LLMOps patterns, and best practices.
Architect and lead the strategy for a centralized Model Context Protocol (MCP) Server.
Evaluate emerging AI technologies, frameworks, and methodologies, making strategic recommendations.

What we offer

Medical
Dental
Vision
Flexible Spending Accounts
Retirement savings plans
Life and disability insurance
Paid vacation & holidays
Tuition assistance programs

Fulltime

Vice President - Technology (Platform Engineer)

Our client's technology team is responsible for creating and continuously improv...

Location

United States , New York

Salary:

175000.00 - 215000.00 USD / Year

Renner Brown

Expiration Date

Until further notice

Requirements

Bachelor's degree in computer science, Computer Engineering, or related field
8+ years in infrastructure engineering, cloud platform engineering, or data engineering
Azure expertise: Azure AI Foundry, Azure Data Factory, Azure Databricks, AKS, Azure API Management, Azure Key Vault, Azure Entra ID
Strong Python skills: backend services, REST APIs (FastAPI or Flask), and automation scripting
PowerShell for infrastructure tasks
Infrastructure-as-Code: Terraform and/or Bicep
container orchestration with Docker and Kubernetes
Experience integrating LLM APIs (Anthropic Claude, Azure OpenAI) in production including token cost management and observability
RAG pipeline experience: vector search (Azure AI Search or pgvector), document processing, and retrieval patterns
Familiarity with LLM application frameworks such as LangChain or Semantic Kernel

Job Responsibility

AI Platform & Developer Infrastructure: Design, build, and operate the firm's AI platform, enabling developers to build and deploy Python-based AI applications
Implement and manage Azure AI Foundry environments: model deployments, AI hubs, project workspaces, and access controls
Integrate and operationalize third-party AI APIs (Anthropic Claude API, Azure OpenAI) with secure access patterns, API gateway controls, rate limiting, and cost monitoring
Build internal developer tooling and SDK scaffolding to accelerate AI application development across the firm
Data Infrastructure & Pipelines: Build and maintain data pipelines using Azure Data Factory and Azure Databricks to serve AI application data needs
Implement vector search and document retrieval infrastructure (Azure AI Search) to support RAG-based applications
Manage structured and unstructured data stores including Azure Data Lake, Azure SQL, and Cosmos DB
Cloud Infrastructure & DevOps: Provision and maintain secure, scalable infrastructure on Azure (primary) and AWS using Infrastructure-as-Code (Terraform or Bicep)
Build and maintain CI/CD pipelines for AI application deployment via Azure DevOps or GitHub Actions
Manage containerized workloads using Docker and Kubernetes (AKS) for AI application hosting and API services

Fulltime