Senior GenAI Architect for Enterprise Solutions

Ex; New York (NY, NJ); Hybrid; USD 150,000 - 170,000; Full time

Job summary

Ex is seeking an AI Architect for Generative AI & Enterprise Solutions in NY/NJ, Hybrid. You will lead end-to-end GenAI architecture, define strategy, and translate complex AI concepts into business value for CXOs.

You will drive production-grade GenAI deployments, select models and toolchains (LangChain, Bedrock), and govern governance, security, and cost optimization across enterprise cloud platforms. Excellent communication required.

Qualifications

• Bachelor's or Master's in CS/Engineering or equivalent practical experience.
• 10+ years in software/AI engineering and architecture with senior leadership.
• Depth in generative AI: LLMs, RAG, agent frameworks.
• Production GenAI experience: design, cost, reliability.
• Hands-on with AWS AI services and cloud infrastructure.

Responsibilities

• Drive the end-to-end architecture and technical vision for generative AI.
• Decide models, frameworks, and agent harnesses balancing capability, latency, cost, and risk.
• Move PoC to production with production-grade designs including orchestration, retrieval (RAG), evaluation, observability, guardrails, and human-in-the-loop.
• Integrate GenAI into existing cloud solutions and CI/CD toolchain for governed capabilities.
• Design for scale and operational excellence for GenAI workloads including token economics and cost optimization.
• Establish the operational foundation with evaluation pipelines, monitoring, drift/quality management, and incident response.

Skills

GenAI expertise

Executive communication

Cloud architecture

RAG & agent frameworks

DevOps tooling

Education

Bachelor's or Master's in CS/Engineering

Tools

LangChain

Amazon Bedrock

Job description

Ex is seeking an AI Architect for Generative AI & Enterprise Solutions in NY/NJ, Hybrid. You will lead end-to-end GenAI architecture, define strategy, and translate complex AI concepts into business value for CXOs.

You will drive production-grade GenAI deployments, select models and toolchains (LangChain, Bedrock), and govern governance, security, and cost optimization across enterprise cloud platforms. Excellent communication required.