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AI Architect

Job in Columbus, Franklin County, Ohio, 43224, USA
Listing for: Virtusa
Full Time position
Listed on 2026-07-06
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Software Architect
Salary/Wage Range or Industry Benchmark: 130000 - 160000 USD Yearly USD 130000.00 160000.00 YEAR
Job Description & How to Apply Below

Job Description - AI Architect (CREQ
256749)

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.

Key Responsibilities
  • 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).
  • 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.
  • 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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