AI Solutions Architect - Enterprise Services

Optimizely

New York (NY)

On-site

USD 129,000 - 220,000

Full time

3 days ago
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Job summary

Optimizely in New York is seeking an AI Solutions Architect to lead architecture, build, and enablement for AI-driven engagements across our Professional Services delivery. You will design reusable agents, integrations, and automation that scale across accounts, ensuring fast value realization for customers.

You will own end-to-end delivery through general availability, then provide background support and continued optimization.

Qualifications

  • You have built and shipped production AI systems: agents, LLM-based workflows, and API integrations.
  • You can design an approach and implement it yourself in AI engineering.
  • You reason about architecture, data, integrations, content, commerce, identity and their seams in delivery ecosystems.
  • You can scope solutions from incomplete requirements and defend your approach under pressure.
  • You understand differences between EMEA and North America delivery and design for cross-region consistency.

Responsibilities

  • Architect AI-driven solutions and reusable patterns across accounts.
  • Lead delivery end-to-end through GA and support thereafter.
  • Document solutions so teams can run, extend, or troubleshoot without you.
  • Drive adoption and gather feedback from internal and Professional Services communities.
  • Collaborate with architects and Delivery to reflect field realities in solutions.

Skills

Generative AI
Cloud & MLOps
Production-grade Python
Systems & integrations
Responsible AI
Optimizely knowledge

Tools

LangChain
LlamaIndex
AWS
Docker
Kubernetes

Job description

Optimizely in New York is seeking an AI Solutions Architect to lead architecture, build, and enablement for AI-driven engagements across our Professional Services delivery. You will design reusable agents, integrations, and automation that scale across accounts, ensuring fast value realization for customers.

You will own end-to-end delivery through general availability, then provide background support and continued optimization.

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