AI Architect - Microsoft Foundry

MAIN PURPOSE :

The AI Architect - Microsoft Foundry will be responsible for designing, governing, and enabling enterprise-grade AI solutions using Microsoft Foundry / Azure AI Foundry as a strategic AI platform within Orbia's global Data, Analytics & AI landscape.

The role exists to ensure that AI agents, copilots, RAG applications, model deployments, enterprise knowledge assistants, and AI-enabled business workflows are designed using secure, scalable, compliant, cost-aware, and reusable architecture patterns.

The architect will work closely with business groups, platform owners, security, infrastructure, integration, data engineering, governance, and external partners to translate AI use cases into production-ready solution architectures.

KEY RESPONSIBILITIES :

Strategy & Planning :

- Define and govern Microsoft Foundry / Azure AI Foundry architecture principles, design standards, and reusable reference patterns for enterprise AI solutions.

- Design and Implement Foundry-led and hybrid Foundry + Databricks solution patterns for copilots, agents, RAG applications, business assistants, and AI-enabled workflows.

- Translate approved business AI use cases into solution architecture documents, platform-fit decisions, integration patterns, and production-readiness plans.

- Define model selection guidance covering accuracy, latency, cost, privacy, security, data sensitivity, and business purpose.

- Establish architecture guardrails for prompt engineering, RAG grounding, tool calling, human-in-the-loop approvals, write-back controls, and auditability.

- Support Orbia AI governance, ARB submissions, decision records, architecture exceptions, and platform standards for Microsoft Foundry solutions.

- Partner with Data, Analytics & AI leadership to align Foundry architecture with Orbia's AI enablement roadmap and scalable operating model.

Acquisition & Deployment :

- Evaluate Microsoft Foundry capabilities, model catalog options, agent frameworks, Azure AI Search, Azure OpenAI, Azure Machine Learning, and adjacent Azure AI services for enterprise fit.

- Collaborate with cloud, infrastructure, network, security, integration, and data platform teams to design DEV / QA / PROD-ready deployment patterns.

- Define secure integration between Foundry agents and enterprise systems including SharePoint, SAP, ServiceNow, Databricks, APIs, Power BI, and internal business applications.

- Design API-led and event-enabled integration patterns using Azure API Management, Entra ID, OAuth, managed identity, service principals, and approved enterprise gateways.

- Lead technical design reviews for Foundry agents, tools, knowledge bases, grounding data, model endpoints, evaluation workflows, monitoring, and release gates.

- Support partner and vendor technical reviews to validate delivery approach, platform compatibility, security posture, and architecture compliance.

Operational Management :

- Define operational runbooks for Foundry agent lifecycle management, prompt/version control, model deployment tracking, evaluations, monitoring, telemetry, and incident support.

- Ensure Foundry solutions follow least-privilege RBAC, access reviews, environment segregation, audit logging, data protection, and responsible AI controls.

- Provide guidance to AI engineers, data engineers, platform admins, business analysts, and implementation partners on approved design and implementation patterns.

- Monitor and optimize solution design for token consumption, Azure AI Search cost, model endpoint usage, latency, quality, security, and scalability.

- Review delivered solutions against architecture principles, Orbia governance expectations, and production acceptance criteria before go-live.

- Continuously improve Foundry architecture standards based on lessons learned, platform roadmap changes, business adoption, and operational feedback.

- Provide application management support for issue and request related to MS foundry services.

EDUCATION, EXPERIENCE, LANGUAGE, & PHYSICAL REQUIREMENTS :

- Academic Level: Bachelor's or academic degree in Computer Science, Information Technology, Engineering, Data Science, Artificial Intelligence, Cloud Computing, or related field.

- Language(s) and level of proficiency: English written and verbal communication at professional working proficiency level.

- Knowledge/Experience: 10 - 12 years of overall IT experience in enterprise architecture, cloud architecture, data architecture, AI/ML engineering, application integration, or digital platforms.

- Minimum 4 years' experience in architecture design across Azure, data platforms, APIs, cloud-native applications, analytics, or AI solutions.

- Minimum 2 years' experience in GenAI, LLM, RAG, agentic AI, AI application architecture, model integration, or enterprise AI platform enablement.

- Hands-on experience or strong architecture knowledge of Microsoft Foundry / Azure AI Foundry, Foundry agents, model deployments, tools, project setup, model catalog, evaluations, monitoring, and prompt orchestration.

- Experience with Azure AI services such as Azure OpenAI, Azure AI Search, Azure Machine Learning, Azure API Management, Azure Monitor, Key Vault, Entra ID, and related Azure services.

- Experience with enterprise data platforms such as Databricks, Delta Lake, Unity Catalog, SQL Warehouses, MLflow, vector search, model serving, or governed data products is strongly preferred.

- Experience designing RAG solutions using SharePoint, enterprise documents, semantic indexes, embeddings, vector search, citations, chunking, grounding evidence, and answer evaluation.

- Experience designing secure enterprise integrations using REST APIs, OAuth 2.0, managed identities, service principals, APIM, event-driven patterns, SAP BTP, ServiceNow APIs, or Microsoft Graph APIs.

- Good understanding of security and governance controls including RBAC, least privilege, segregation of duties, access reviews, private endpoints, audit logging, DLP, Purview, data classification, and SOX / ITGC expectations.

- Experience in AI governance, responsible AI, model evaluation, prompt engineering, hallucination control, content safety, human approval gates, and production release criteria.

- Experience preparing architecture review documents, solution design documents, technical standards, operating procedures, decision records, and ARB-ready materials.

- Good understanding of cost management for AI solutions including token usage, model cost, search cost, storage, compute, monitoring, model endpoints, and FinOps guardrails.

- Experience in working in an international environment at a global company with cross-functional teams and business stakeholders.

- Excellent communication skills in English, both verbally as well as in writing.

- Capabilities to build trustworthy relationships with business users, platform teams, security, architecture, vendors, and implementation partners.

- Self-starter with the ability to provide technical leadership, mobilize business partners, analyze requirements, challenge solution assumptions, push back when required, and remain result-oriented.

- Willingness to travel, if required, as per project and business needs.

Skills

Machine Learning, Artificial Intelligence, Azure, Data Engineering, Technical Architect, AI Architecture, LLM, RAG, Databricks