AI Architect – Generative AI, Enterprise Solutions

Jobtailor

New Jersey

On-site

USD 180,000 - 240,000

Full time

14 days+

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Job summary

Jobtailor seeks an engineering leader to drive the end-to-end GenAI architecture and technical vision across the enterprise. You will select models, frameworks, and agent harnesses to balance capability, latency, cost and risk, guiding teams from PoC to production with scalable designs and proper governance.

You will mentor engineers, shape the GenAI strategy, and communicate business value to CXO-level stakeholders while ensuring security and compliance throughout the architecture.

Qualifications

Degree in Computer Science or Engineering or equivalent experience.
10+ years in software/AI engineering and architecture with senior leadership.
Proven GenAI track record: LLMs, RAG, agent frameworks and production-scale design.
Deep AWS experience and cloud infra knowledge.
Strong enterprise architecture, DevOps and security awareness.

Responsibilities

Drive end-to-end GenAI architecture and technical vision for the function.
Make authoritative technology decisions on models, frameworks, and harnesses.
Move PoC to production with scalable, observable designs and guardrails.
Integrate GenAI into cloud solutions and automation platforms.
Design for scale, throughput, latency, and cost optimization.
Establish governance, evaluation pipelines, and incident response.
Embed security, privacy, responsible AI, and compliance into architecture.
Advise CXO-level leaders on business value, trade-offs, and roadmaps.
Shape enterprise GenAI strategy and ROI analyses.
Mentor engineering teams and define architecture governance.

Skills

Generative AI Architecture

LLMs

Prompt Engineering

RAG

Agent Frameworks

Production-Grade Design

Cost Optimization

Evaluation Pipelines

Monitoring & Incident Response

Data Privacy

Security

Education

Bachelor's Degree in Computer Science

Master's Degree in Engineering

Tools

AWS

GitHub

Jenkins

Artifactory

SonarQube

Job description

Drive the end-to-end architecture and technical visionfor 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 productionwith realistic, production-grade designs – covering orchestration, retrieval (RAG), evaluation, observability, guardrails, and human-in-the-loop.
Integrate GenAIinto 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 excellencefor GenAI workloads – throughput, latency, reliability, and cost optimization (token economics, caching, model routing).
Establish the operational foundationincluding evaluation pipelines, monitoring, drift/quality management, and incident response for Agentic solutions.
Bake in guardrailssuch as security, data privacy, responsible-AI, hallucination mitigation, and regulatory compliance into every architecture.
Advise and influenceto CXO-level leaders, translating complex AI concepts into clear business value, trade-offs, risks, and roadmaps.
Shape the generative-AI strategy and roadmapfor the enterprise, aligning technology investment with business outcomes and priorities.
Build and presentbusiness 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 upskillengineering teams and set architecture governance, review gates, and reusable building blocks.
Define and stewardAI governance, standards, and best practices in partnership with security, data, and legal.

Requirements

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

Core Competencies

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.

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