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AI Architect – Generative AI & Enterprise Solutions

Job in Washington, District of Columbia, 20001, USA
Listing for: EXL
Full Time position
Listed on 2026-08-05
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 150000 - 170000 USD Yearly USD 150000.00 170000.00 YEAR
Job Description & How to Apply Below

Architecture-Cloud Architecture

Work Location:

NY/NJ

Work Mode:
Hybrid (2-3 days onsite)

Pay Range: $150K-$170K /Yr Base + Annual Bonus

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.

Responsibilities

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.

Running AI at Scale

  • 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., Lang Chain, 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 Dev Ops toolchain (Git Hub, Jenkins, Artifactory, Sonar Qube).
  • 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.
Required Skills
  • Attention To Consistency
  • Internal Communications
  • Interpersonal Relationship Building
  • Lead Identification
  • Leadership Capabilities
  • Microsoft Office
  • Salesforce Administration
  • Working under Pressure
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