AI Architect – Generative AI & Enterprise Solutions

EXL; New Jersey; On-site; USD 170,000 - 250,000; Full time

Job summary

EXL seeks an AI Architect to lead the GenAI strategy and technical vision across cloud and automation platforms. You will drive reference architectures, select models and frameworks, and ensure production-grade deployments at scale for enterprise AI initiatives.

You will influence CXO-level stakeholders, translate complex AI concepts into business value, and establish governance, guardrails, and cost-aware design across AWS Bedrock and related services.

Qualifications

• Bachelor's or Master's degree in CS, Engineering, or related field.
• 10+ years of software/AI engineering and architecture experience.
• Proven GenAI production experience at scale.
• Deep AWS and cloud infra knowledge (e.g., Bedrock).
• Enterprise architecture, integration and modern DevOps tooling.

Responsibilities

• Define end-to-end GenAI architecture and technical vision.
• Decide models, frameworks, and agent harnesses balancing cost and risk.
• Productionize GenAI with observability, guardrails, and human-in-the-loop.
• Integrate GenAI into AWS, CI/CD, and ITSM toolchains.
• Design for scale, throughput, latency, and cost optimization.
• Engage CXO-level stakeholders and shape enterprise AI strategy.
• Establish governance, standards, and best practices for AI.

Skills

Generative AI

LLMs

Prompt engineering

RAG

Agent frameworks

Executive communication

Education

Bachelor's or Master's degree in CS/Engineering/related field

Tools

GitHub

Jenkins

Artifactory

SonarQube

Job description

We are seeking an AI Architect to help build the technical vision and architecture for generative AI across the Global Technology Commercial Cloud practice. Sitting within the Global Technology organization that runs our AWS cloud environments for commercial solutions, automation platform (GitHub, Jenkins, Artifactory, SonarQube), and cloud operations, you will define how we design, deploy, and operate GenAI solutions at scale – safely, reliably, and cost-effectively.

Responsibilities:

This is a senior, highly visible role that blends deep technical mastery with executive influence. You are expected to be a recognized expert in generative AI – frameworks, agent harnesses, and the realities of production deployment – and equally comfortable in the boardroom, translating complex technology into clear business value for CXO-level stakeholders and helping shape enterprise AI strategy.

Architecture & Technical Leadership

• 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.

Executive Engagement & Strategy

• 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.

Enablement & Governance

• 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.

Qualifications:

• 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.