Senior AI Systems Architect — Embedded, Production-Ready ML

Amazon Inc.; Seattle (WA); On-site; USD 168,000 - 227,000; Full time

Job summary

Amazon is seeking a Senior Forward Deployed Engineer to lead custom generative AI model work on customer engagements. You will define strategic direction, supervise model optimization, and ensure production readiness across distributed training and inference workloads.

You will mentor teams, drive architectural trade-offs, and coordinate with AWS services to scale complex AI deployments, balancing quality, latency and cost.

Qualifications

• 5+ years of non-internship professional software development experience.
• Experience as a mentor, tech lead or leading an engineering team.
• Hands‑on experience training, fine‑tuning, or optimizing deep learning models.
• Experience communicating technical concepts to both technical and non‑technical audiences, including senior leadership.

Responsibilities

• Lead the technical engagement: embed with the customer as the technical lead for model customization and optimization.
• Define the customization strategy: decide the right path to quality, latency, and cost targets.
• Architect training and inference systems at scale for large models and multi‑adapter serving.
• Lead migrations of training/inference workloads to AWS Trainium and optimize performance.
• Mentor FDEs and scientists, lead design reviews and contribute to hiring.
• Identify reusable patterns and influence AWS service roadmaps.
• Oversee engagement execution: deliver milestones and ensure deliverables.

Skills

Software dev 5+ yrs

Mentor/Tech lead

Model fine-tuning

Communication to leadership

Education

BS CS or equivalent

Tools

PyTorch FSDP2

Megatron-LM

Miles

verl

Job description

Amazon is seeking a Senior Forward Deployed Engineer to lead custom generative AI model work on customer engagements. You will define strategic direction, supervise model optimization, and ensure production readiness across distributed training and inference workloads.

You will mentor teams, drive architectural trade-offs, and coordinate with AWS services to scale complex AI deployments, balancing quality, latency and cost.