AI Architect – Generative AI, Enterprise Solutions

EXL

AI Architect designing generative AI solutions within the commercial cloud practice for enterprise applications. Collaborating with stakeholders to translate technical strategies into business value.

Posted 7/22/2026full-timeNew Jersey, New York • 🇺🇸 United StatesSeniorLead💰 $150,000 - $170,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in generative AI architecture and implementation, with a strong focus on AWS cloud solutions, operational excellence, and AI governance. Capable of translating complex AI concepts into business value while mentoring engineering teams and influencing executive leadership.

Highest-signal resume keywords

Generative AI ArchitectureAWS AI ServicesLarge-Scale Systems DesignAI Governance and ComplianceExecutive Communication

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Generative AILLMsPrompt EngineeringRAGAgent FrameworksProduction-Grade DesignCost OptimizationEvaluation PipelinesMonitoring and Incident ResponseData Privacy

Soft Skills

Exceptional CommunicationExecutive PresenceMentoring

Tools & Technologies

AWSGitHubJenkinsArtifactorySonarQube

Certifications & Qualifications

Bachelor's Degree in Computer ScienceMaster's Degree in Engineering

Industry Keywords

AI EngineeringEnterprise ArchitectureDevOpsSecurityData Governance

Tech Stack

Tools & technologies

AWSCloudITSMJenkins

About the role

Key responsibilities & impact

Drive the end-to-end architecture and technical vision for generative AI within the function – reference architectures, patterns, and standards that teams build against.
Make authoritative technology decisions, selecting the right models, frameworks, and agent harnesses for each use case, balancing capability, latency, cost, and risk.
Move solutions from proof-of-concept to production with realistic, production-grade designs – covering orchestration, retrieval (RAG), evaluation, observability, guardrails, and human-in-the-loop.
Integrate GenAI into the existing cloud solutions and automation platform (AWS, CI/CD toolchain, ITSM) so GenAI is a first-class, governed capability.
Design for scale and operational excellence for GenAI workloads – throughput, latency, reliability, and cost optimization (token economics, caching, model routing).
Establish the operational foundation including evaluation pipelines, monitoring, drift/quality management, and incident response for Agentic solutions.
Bake in guardrails such as security, data privacy, responsible-AI, hallucination mitigation, and regulatory compliance into every architecture.
Advise and influence to CXO-level leaders, translating complex AI concepts into clear business value, trade-offs, risks, and roadmaps.
Shape the generative-AI strategy and roadmap for the enterprise, aligning technology investment with business outcomes and priorities.
Build and present business cases, ROI, and build-vs-buy analyses for AI initiatives.
Serve as an evangelist and trusted expert – to executives, engineering teams, and external partners – and champion an enterprise AI vision.
Mentor and upskill engineering teams and set architecture governance, review gates, and reusable building blocks.
Define and steward AI governance, standards, and best practices in partnership with security, data, and legal.

Requirements

What you’ll need

Bachelor's or Master's degree in Computer Science, Engineering, or a related field – or equivalent practical experience.
10+ years of experience in software/AI engineering and architecture, including senior technical leadership on large-scale systems.
Recognized depth in generative AI: LLMs, prompt/context engineering, RAG, agent frameworks (e.g., LangChain, Amazon Bedrock Agents), and agent harnesses.
Proven track record designing and running GenAI solutions in production at scale – including evaluation, observability, cost, and reliability.
Deep hands-on knowledge of AWS and its AI services (e.g., Amazon Bedrock), plus core cloud infrastructure (compute, networking, IAM, containers).
Strong grounding with enterprise architecture practices, integration, and the modern DevOps toolchain (GitHub, Jenkins, Artifactory, SonarQube).
Exceptional communication and executive-presence skills – able to hold credible, persuasive CXO-level conversations and articulate complex technology in business terms.
Solid understanding of responsible-AI, security, and data-governance considerations for enterprise AI.

Benefits

Comp & perks

For more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits