AI Architect

What Working at Hexaware offers:

Hexaware is a dynamic and innovative IT organization committed to delivering cutting-edge solutions to our clients worldwide. We pride ourselves on fostering a collaborative and inclusive work environment where every team member is valued and empowered to succeed.

Hexaware provides access to a vast array of tools that enhance, revolutionize, and advance professional profile. We complete the circle with excellent growth opportunities, chances to collaborate with highly visible customers, chances to work alongside bright brains, and the perfect work-life balance.

With an ever-expanding portfolio of capabilities, we delve deep into and identify the source of our motivation. Although technology is at the core of our solutions, it is still the people and their passion that fuel Hexaware s commitment towards creating smiles.

At Hexaware we encourage to challenge oneself to achieve full potential and propel growth. We trust and empower to disrupt the status quo and innovate for a better future. We encourage an open and inspiring culture that fosters learning and brings talented, passionate, and caring people together.

We are always interested in, and want to support, the professional and personal you. We offer a wide array of programs to help expand skills and supercharge careers. We help discover passion the driving force that makes one smile and innovate, create, and make a difference every day.

The Hexaware Advantage: Your Workplace Benefits
Health benefits with low-cost employee premium.
Range of voluntary benefits such as Legal, Identity theft and Critical Care Coverage training and upskilling opportunities through Udemy and Hexavarsity

Senior AI Architect (Agentic AI & Multi-Agent Platforms)
Location: Remote

Position Summary
5+ Years in AI/ML & GenAI Architecture. We are seeking a highly experienced Senior AI Architect to lead the design and implementation of an enterprise-scale Agentic AI platform that enables autonomous and semi-autonomous AI agents across business functions.

12+ Years Overall The ideal candidate will architect and deliver a scalable multi-agent ecosystem leveraging Microsoft Azure, Azure OpenAI, Copilot Studio, Power Platform, RAG architectures, SAP integrations, MCP (Model Context Protocol), and enterprise knowledge platforms.
Key Responsibilities
Define enterprise architecture for multi-agent AI systems and agent orchestration frameworks.
Design AI agent ecosystems capable of autonomous reasoning, planning, tool usage, and workflow execution.
Establish standards for agent lifecycle management, memory, prompts, governance, and observability.
Architect Planner, Orchestrator, Domain, Tool, Knowledge, and Validation Agents.
Design enterprise RAG platforms and knowledge ingestion frameworks.
Integrate SAP ECC/S4HANA, SAP APIs, SAP BTP, Peoplesoft and on-prem systems.
Lead Azure OpenAI, Copilot Studio, Power Platform, Dataverse, and Azure integration architecture.
Design MCP-based tool, resource, and prompt exposure frameworks.
Implement AI governance, security, compliance, monitoring, and guardrails.
Required Qualifications
12+ years of software, cloud, integration, or enterprise architecture experience.
5+ years designing AI/ML solutions.
2+ years working with Generative AI and Agentic AI platforms.
Strong expertise in Azure OpenAI, Copilot Studio, Power Platform, Azure Functions, API Management, and Container Platforms.
Experience with SAP integrations, REST APIs, Event-Driven Architecture, and Service BKafka.
Proficiency in Python, C#, and JavaScript/TypeScript.

Preferred Qualifications
Experience implementing MCP (Model Context Protocol).
Experience with LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar frameworks.
Experience building AI copilots and autonomous workflow agents.
Experience with Microsoft Cloud and enterprise data platforms.
Azure AI certifications (AI-102, Azure Solutions Architect) preferred.
Success Criteria (First 6 12 Months)
Establish enterprise Agentic AI reference architecture.
Deliver a scalable multi-agent framework.
Implement MCP-enabled enterprise tool ecosystem.
Build enterprise RAG platform integrated with SAP, Peoplesoft and internal business systems.
Define governance, security, and observability standards.
Create reusable AI accelerators and implementation playbooks.

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