The Role
Architects and delivers enterprise AI platforms, advanced analytics solutions, and scalable cloud-native architectures. Translates business requirements into secure, production-ready AI systems using Azure AI technologies. Defines patterns for generative AI, machine learning, intelligent applications, governance, MLOps, and operationalization. Collaborates with business, data, engineering, and platform teams, establishes architecture standards, evaluates emerging technologies, and guides AI initiatives from ideation through implementation.
Summary Generated by Built In
Architect
Job requirements
- Architect and deliver enterprise AI platforms and advanced analytics solutions that align with business objectives and drive measurable outcomes
- Translate complex business use cases into scalable AI, analytics, and technology architectures leveraging modern cloud and AI capabilities
- Design and implement AI solutions utilizing Azure Foundry, Azure AI services, and cloud-native technologies to ensure scalability, security, and production readiness
- Define architecture patterns and frameworks for Generative AI, machine learning, advanced analytics, and intelligent applications
- Collaborate with business, data, engineering, and platform teams to drive AI initiatives from ideation through implementation
- Establish standards and best practices for AI platform engineering, integration, governance, security, and operationalization
- Evaluate emerging AI platform capabilities and technologies to identify opportunities for improving business outcomes
- Provide architectural guidance to delivery teams and stakeholders to ensure AI investments are aligned with enterprise priorities
- Microsoft Azure AI technologies, including Azure Foundry and Azure AI services
- Designing scalable, secure, and production-ready AI and analytics solutions
- Generative AI, machine learning, and advanced analytics architectures
- Enterprise cloud platforms and data platform engineering
- API design, integration patterns, and modern AI solution architectures
- AI governance, security, responsible AI, and operationalization best practices
- MLOps and AI platform automation
- Leading enterprise AI transformation and platform modernization initiatives
- GenAI patterns, including LLM applications, Retrieval-Augmented Generation (RAG), agents, prompt engineering, and AI orchestration
- Building reusable AI platforms and accelerators for enterprise-scale adoption
- LLMOps, AI observability, and model lifecycle management
- Connecting AI platform capabilities to measurable business outcomes
- Bachelor's degree in Computer Science, Information Technology, Data Science, or a closely related discipline
- Microsoft Certified: Azure Solutions Architect Expert
- Microsoft Certified: Azure AI Engineer Associate
Experience Range: With at least 7 to 10 years of experience in AI, advanced analytics, cloud platforms, and solution architecture, including demonstrated expertise in translating business requirements into scalable, secure, production-ready AI solutions Key Responsibilities:
Required Skills:
Preferred Skills:
Desired Qualifications:
Skills Required
- At least 7 to 10 years of experience in AI, advanced analytics, cloud platforms, and solution architecture
- Experience translating business requirements into scalable, secure, production-ready AI solutions
- Microsoft Azure AI technologies, including Azure Foundry and Azure AI services
- Designing scalable, secure, and production-ready AI and analytics solutions
- Generative AI, machine learning, and advanced analytics architectures
- Enterprise cloud platforms and data platform engineering
- API design, integration patterns, and modern AI solution architectures
- AI governance, security, responsible AI, and operationalization best practices
- MLOps and AI platform automation
- Leading enterprise AI transformation and platform modernization initiatives
- GenAI patterns including LLM applications, RAG, agents, prompt engineering, and AI orchestration
- Building reusable AI platforms and accelerators for enterprise-scale adoption
- LLMOps, AI observability, and model lifecycle management
- Connecting AI platform capabilities to measurable business outcomes
- Bachelor's degree in Computer Science, Information Technology, Data Science, or a closely related discipline
- Microsoft Certified: Azure Solutions Architect Expert
- Microsoft Certified: Azure AI Engineer Associate
Brillio Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Brillio and has not been reviewed or approved by Brillio.
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Healthcare Strength — Healthcare is considered comprehensive, including medical coverage for employees and dependents alongside life, disability, and accidental death protections. Feedback suggests these protections are a core strength of the package.
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Leave & Time Off Breadth — Time-off options include paid leave and parental leave, with flexible or ‘flexible PTO’ approaches cited in some contexts. Feedback suggests this breadth helps support work-life balance when team norms permit usage.
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Wellbeing & Lifestyle Benefits — Wellbeing offerings span counseling, financial-management sessions, fitness programs, and travel insurance, plus region-specific extras like discounted IT hardware and work-from-home essentials. Feedback suggests these add-ons enhance perceived value beyond core insurance.
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The Company
What We Do
Brillio is the leader in global digital business transformation, applying technology with a human touch. We help businesses define internal and external transformation objectives, and translate those objectives into actionable market strategies using proprietary technologies. With 2600+ experts and 13 offices worldwide, Brillio is the ideal partner for enterprises that want to quickly increase their core business productivity, and achieve a competitive edge, with the latest digital solutions.
