AI Architect – Microsoft Foundry

Orbia Pune; Pune District; On-site; INR 4,500,000 - 7,000,000; Full time

Job summary

Orbia Pune seeks an AI Architect – Microsoft Foundry to design, govern, and enable enterprise-grade AI solutions across Orbia's global Data, Analytics & AI landscape.

The role requires translating AI use cases into production-ready architectures, aligning with governance, security, and cost controls while collaborating with business groups and partners.

Qualifications

• Bachelor’s degree in CS, IT, Eng, Data Science, AI, Cloud Computing, or related field.

Responsibilities

• Define and govern Foundry architecture principles, design standards, and reusable reference patterns for enterprise AI solutions.

Skills

Enterprise AI architecture

Foundry / Azure AI Foundry

AI governance

RAG solutions design

Security & compliance

Stakeholder collaboration

Cost optimization

Token optimization

Education

Bachelor’s degree in Computer Science or related field

Tools

Microsoft Foundry

Azure OpenAI

Azure ML

Databricks

Azure API Management

Job description

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.

2. KEY RESPONSIBILITIES

The AI Architect – Microsoft Foundry will be responsible for:

• 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.