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AI Architect

Job in Columbus, Franklin County, Ohio, 43215, USA
Listing for: Virtusa
Full Time position
Listed on 2026-07-03
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Software Architect
Job Description & How to Apply Below

Systems Architect (Level: Senior Manager)

We are seeking experienced AI Architects to join a centralized AI Center of Excellence (CoE), responsible for driving enterprise-wide AI transformation. This role focuses on embedding agentic AI into delivery models and the end-to-end SDLC, while defining governance, standards, and scalable AI frameworks in a highly regulated environment. The architect will act as a strategic authority and hands-on leader, ensuring consistent, secure, and high-quality AI implementations across client-facing and internal platforms.

AI-Driven SDLC Transformation:
Design AI-first delivery models across requirements, development, testing, and deployment. Integrate AI agents into Dev Ops/CI-CD pipelines and define measurable productivity KPIs (cycle time, defect reduction, velocity).

Agentic AI Architecture:
Design and implement multi-agent systems using frameworks like Lang Chain, Auto Gen, and CrewAI. Define agent patterns (planner-executor, tool-using agents, critic loops) and ensure observability, explainability, and guardrails.

AI Platform & Framework Development:
Build reusable accelerators, playbooks, and reference architectures. Establish standards for prompt engineering, RAG, model selection, and evaluation. Enable self-service AI platforms using cloud ecosystems like Amazon Web Services and Microsoft Azure.

Preferred Qualifications:

  • Financial services domain experience
  • Experience building internal developer platforms (IDPs)
  • Cloud certifications (AWS/Azure/GCP)
  • Exposure to spec-driven AI development and AI playbooks

Required Qualifications:

  • 12+ years in software engineering/architecture; 5+ years in AI/ML
  • Strong hands-on experience with GenAI, LLMs, and agentic AI systems
  • Expertise in RAG, embeddings, prompt engineering, and evaluation frameworks
  • Experience with distributed systems, APIs, microservices, and Kubernetes
  • Familiarity with MLOps/LLMOps pipelines and cloud AI platforms
  • Experience working in regulated environments (financial services preferred)
  • Strong understanding of AI governance, model risk, and data privacy
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