Senior Enterprise AI Architect (Hybrid)

Prattwhitney

Farmington (CT)

Hybrid

USD 132,000 - 252,000

Full time

14 days+

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Job summary

RTX Enterprise Services seeks an experienced AI Architect to define and guide enterprise AI/ML architectures across RTX. You will partner with business units, product teams, engineering, cybersecurity, data, and enterprise technology to translate complex needs into scalable AI architectures.

This role focuses on reusable capabilities, reference architectures, and design patterns. The ideal candidate combines deep AI/ML expertise with software, cloud, and enterprise architecture experience,

Qualifications

  • University degree in CS/AI/ML/engineering or related STEM with ≥10 years, or advanced degree with ≥7 years.
  • Minimum 5 years designing AI/ML in production environments.
  • Experience as technical architect or lead for enterprise software, data, or AI/ML systems.

Responsibilities

  • Define end-to-end architectures for enterprise AI/ML across data, apps, APIs, and platforms.
  • Translate business needs into architecture blueprints, roadmaps, and success criteria.
  • Select approaches (traditional software, ML, GenAI, RAG, agentic AI) for complex problems.
  • Create reusable reference architectures, patterns, and guardrails across RTX units.
  • Architect AI solutions including model routing, grounding, memory, and human-in-the-loop workflows.
  • Define data pipelines, model serving, MLOps, and deployment across cloud and on-prem.
  • Lead architecture reviews and mentor engineering teams on security and governance.

Skills

AI/ML architecture
Generative AI
Distributed systems
Cloud platforms
Security concepts
Kubernetes
CI/CD
MLOps

Education

Bachelor's degree in CS/AI/ML/engineering or related STEM
Advanced degree in related field

Tools

Kubernetes
Cloud platforms (AWS/GCP/Azure)
DevOps tools

Job description

RTX Enterprise Services seeks an experienced AI Architect to define and guide enterprise AI/ML architectures across RTX. You will partner with business units, product teams, engineering, cybersecurity, data, and enterprise technology to translate complex needs into scalable AI architectures.

This role focuses on reusable capabilities, reference architectures, and design patterns. The ideal candidate combines deep AI/ML expertise with software, cloud, and enterprise architecture experience,

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