As an AI Integration Engineer, you will join a dynamic team responsible for designing and maintaining infrastructure that supports advanced AI systems, including Large Language Models (LLMs) and distributed workloads. Your day-to-day responsibilities include architecting scalable GPU computing environments, managing CI/CD pipelines for AI deployments, ensuring seamless network connectivity between distributed systems, and providing diagnostic expertise to maintain system performance. You will leverage cloud platforms like AWS, Azure, or Google Cloud, along with tools such as MLflow, Kubeflow, and Kubernetes, to integrate MLOps pipelines and manage stateful databases. Ideal candidates have 5+ years of experience in infrastructure engineering, a strong background in high-performance computing, and expertise in NVIDIA GPU technologies and container orchestration. This role offers the opportunity to work on cutting-edge AI projects at scale, contributing to the seamless integration of complex AI systems into operational workflows.
Skills
AWS
Azure
Google Cloud
SageMaker
GCP AI Platform
Azure Machine Learning
MLflow
Kubeflow
TensorFlow Serving
Vertex AI
LangSmith
Arize Phoenix
LangGraph
CrewAI
AutoGen
Redis
Postgres
Kubernetes
Docker
Terraform
CUDA
NCCL
TensorRT
NGINX
Prometheus
Grafana
PyTorch
Hugging Face Transformers
Ray
Horovod
Dask
What you'll do
Design and maintain scalable GPU computing environments for autonomous agentic workflows.
Develop and manage CI/CD pipelines for seamless transitions of AI models to production.
Ensure network connectivity and security between distributed systems, GPUs, VMs, APIs, and C2 tools.
Provide diagnostic expertise and monitor infrastructure to maintain performance benchmarks.
Integrate MLOps pipelines using tools like MLflow, Kubeflow, TensorFlow Serving, and Vertex AI.
What we're looking for
5+ years of experience in infrastructure engineering or system integration roles.
2+ years supporting large-scale AI/ML systems and GPU-centric environments.
Experience with cloud platforms like AWS, Azure, Google Cloud, and their AI services.
Proficiency in integrating MLOps pipelines using tools such as MLflow, Kubeflow, TensorFlow Serving.
Expertise in managing distributed, high-performance computing environments with GPUs and cloud instances.
Knowledge of NVIDIA GPU technologies including CUDA, NCCL, TensorRT, and DGX systems.
Market check
Salary context
This
$112,800–$257,000
range sits above
37%
of similar postings on FindRole.
Peer median band
$158,400–$240,800
Median floor and ceiling across peers.
Typical midpoint (25–75%)
$159,750–$246,150
Middle half of comparable postings.
Based on 240 comparable postings.*
* 240 is the maximum number of comparable postings sampled.
Employer
About Booz Allen Hamilton
Booz Allen Hamilton is a management and technology consulting firm that provides analytics, digital, engineering, and cybersecurity solutions primarily to U.S. government agencies and commercial clients. Industry: Management & Technology Consulting
Booz Allen Hamilton currently has
627 open roles
on FindRole.
Listed pay typically runs
$86,800–$198,000
across 614 roles with salary data.