AI Architect

Job Description

W-2 Open Positions Need to be Filled Immediately. Consultant must be on our company payroll, Corp-to-Corp (C2C) is not allowed.

Candidates encouraged to apply directly using this portal. We do not accept resumes from other company/ third-party recruiters -->

Job Overview

Job ID: J53145

Posted Date: 01/30/2026

--> Specialized Area: Machine learning

--> Job Title: AI Architect

Location: Hoboken, NJ

Duration: 24 Months + Extension

Hourly Rate: Depending on Experience (DOE)

Domain Exposure: Healthcare, Banking & Finance, Insurance, Telecom, Education, IT/Software

--> Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, L2-EAD, GC-EAD

Client: To Be Discussed Later

Employment Type: W-2, 1099, C2C Bench Recruiter: Jessy Thomas

-->

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Job Description : Role Overview Virtusa AI Labs is seeking an AI Solution Lead who can design, build, and operationalize next-generation AI applications that deliver measurable business impact. This client-facing role blends AI and solution development to help enterprises move from AI experimentation to large-scale adoption. As part of a high-impact, client-embedded engineering team, you will help transform business requirements into production-grade AI systems, spanning GenAI applications, predictive modeling, and agentic AI systems. Youll work alongside Virtusas data, product, and cloud experts to bring cutting-edge AI research into the enterprise world responsibly and at scale. If you thrive at the intersection of AI innovation, solution architecture, and business value creation, this is your opportunity to help shape the future of applied AI. Key Responsibilities 1 Solution Design & Development Collaborate with client and internal teams to design end-to-end AI solutions using modern architectures and best practices. - Translate business problems into deployable systems using techniques like retrieval-augmented generation (RAG), multi-agent orchestration, and hybrid reasoning pipelines. 2 Full-Cycle AI Engineering Own the full AI lifecycle from data ingestion and preparation through model integration, solution evaluation, and production deployment. - Apply MLOps, LLMOps, and FMOps principles to automate workflows, manage versions, and ensure robust, repeatable deployments. Experience: Overall 10+ years with 4+ years of experience in a solution architect, or technical consulting role within the AI/ML domain. Technical Acumen: Solid understanding of AI/ML concepts, frameworks (e.g., TensorFlow, PyTorch), and cloud platforms (e.g., AWS, Azure, GCP). Hands-on experience with LLMs and agentic AI Communication: Exceptional verbal and written communication skills with the ability to present complex ideas clearly and persuasively.

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