Lead AI Architect: GenAI & Scalable Solutions

GE Aerospace; Warszawa; Hybrid; PLN 300,000 - 540,000; Full time

Benefits offered by this job

Flexible work schedule

Hybrid work model

Competitive salary and annual bonus

Global opportunities

Job summary

GE Aerospace Warsaw campus is seeking an experienced AI Architect to lead the design, development, and industrialization of advanced AI solutions across the organization. You will shape AI capabilities that deliver measurable business value, partnering with data scientists, engineers and product teams.

The role requires deep expertise in machine learning, generative AI, MLOps, and responsible AI, with hands-on delivery across the full lifecycle from discovery to production.

Qualifications

• Degree in Computer Science, Data Science, AI, Engineering, Mathematics, Statistics, or related field.
• Proven experience designing AI solutions in production environments at scale.
• Experience across the AI lifecycle from ideation to deployment.
• Strong knowledge of Generative AI and LLM orchestration.
• Experience with cloud AI/ML ecosystems (Azure/AWS/GCP).
• Understanding of security, scalability, and modularity in architectures.

Responsibilities

• Define end-to-end AI and GenAI architectures across ML, NLP, multimodal, and agentic systems.
• Lead AI solution development across full lifecycle: discovery, prototyping, deployment, production support.
• Mentor multidisciplinary teams and promote AI engineering best practices.
• Engage stakeholders to identify high-value AI opportunities and present proposals.

Skills

Generative AI

LLM architecture

Agentic workflows

Prompt design

Cloud AI/ML ecosystems

Data pipelines & API integrations

Solution architecture principles

Education

Degree in Computer Science or related field

Tools

Azure

AWS

GCP

Job description

GE Aerospace Warsaw campus is seeking an experienced AI Architect to lead the design, development, and industrialization of advanced AI solutions across the organization. You will shape AI capabilities that deliver measurable business value, partnering with data scientists, engineers and product teams.

The role requires deep expertise in machine learning, generative AI, MLOps, and responsible AI, with hands-on delivery across the full lifecycle from discovery to production.