AI Architect & Lead Developer | Hybrid Seattle

Capgemini Engineering; Seattle (WA); Hybrid; USD 82,082 - 193,440; Full time

Benefits offered by this job

Paid time off

Medical, dental, vision coverage

Retirement savings plans

Life and disability insurance

Employee assistance programs

Local policy benefits

Job summary

Capgemini Engineering is seeking a highly skilled AI Architect/Developer in Seattle, hybrid to bridge AI strategy and production-grade implementation. Lead design of scalable AI ecosystems, select model architectures, and contribute to custom AI solutions and pipelines.

You will translate business needs into robust blueprints, write maintainable production code, and mentor junior staff while adhering to secure AI practices in an Agile environment.

Qualifications

• 10+ years of enterprise AI/ML architecture experience.
• Experience selecting LLMs/SLMs and traditional ML models based on latency, cost, and accuracy.

Responsibilities

• Translate business requirements into scalable AI architectural blueprints.
• Write clean, modular production code in Python.
• Conduct model tuning, quantization, and pruning for performance.
• Mentor junior staff and ensure secure coding practices.
• Work within an Agile/Scrum framework with delivery milestones.
• Maintain architectural documentation and API specifications.

Skills

AI architecture design

Enterprise AI/ML

Mentoring

Agile/Scrum

Code quality & security

Education

Bachelor's degree in a technical field

Tools

PyTorch

TensorFlow

LangChain

LlamaIndex

MLflow

Kubeflow

Docker

Kubernetes

FastAPI

Flask

Airflow

Kafka

Spark

Job description

Capgemini Engineering is seeking a highly skilled AI Architect/Developer in Seattle, hybrid to bridge AI strategy and production-grade implementation. Lead design of scalable AI ecosystems, select model architectures, and contribute to custom AI solutions and pipelines.

You will translate business needs into robust blueprints, write maintainable production code, and mentor junior staff while adhering to secure AI practices in an Agile environment.