Senior Principal AI/ML Platform Architect

Archer; Jersey City (NJ); On-site; USD 180,000 - 250,000; Full time

Job summary

Archer, in collaboration with JPMorganChase, seeks a Senior Principal Software Engineer to lead ML engineering across cloud/on-prem environments, focusing on scalable, secure AI products. You will drive LLM/GNN deployments, ML tooling, and governance while collaborating with diverse teams to deliver impactful technology.

You will leverage deep engineering expertise in Python, DL frameworks, and MLOps to optimize performance, reliability, and cost efficiency at enterprise scale.

Qualifications

• 10+ years of applied software engineering experience.
• 8+ years AI/ML engineering with LLMs, GNNs and related architectures.

Responsibilities

• Advises on strategy, architecture, and development of model-serving solutions across cloud/on-prem environments.
• Defines MLOps and LLMOps for end-to-end model lifecycle management.
• Drives low-latency, high-throughput model inferencing optimization.
• Sets standards for agentic AI-enabled engineering across a portfolio.
• Applies SDLC tooling to improve automation and delivery at scale.
• Creates reusable software/frameworks to standardize ML Engineering services.
• Leads deployment and optimization using model inference servers (Triton, vLLM).
• Partners with data science, platform engineering, and SRE to productionize models on AWS.

Skills

AI/ML engineering

LLMs

GNNs

Python

Distributed systems

Communication

SRE collaboration

Observability

System design

Education

Master's in CS/Engineering

PhD (optional)

Tools

SageMaker

Bedrock

EKS

Azure ML

GCP Vertex AI

Triton Inference Server

vLLM

PyTorch

TensorFlow

Hugging Face Transformers

MLflow

SageMaker Pipelines

Kubeflow

Docker

Kubernetes

Terraform

CloudFormation

Job description

Archer, in collaboration with JPMorganChase, seeks a Senior Principal Software Engineer to lead ML engineering across cloud/on-prem environments, focusing on scalable, secure AI products. You will drive LLM/GNN deployments, ML tooling, and governance while collaborating with diverse teams to deliver impactful technology.

You will leverage deep engineering expertise in Python, DL frameworks, and MLOps to optimize performance, reliability, and cost efficiency at enterprise scale.