Senior AI Engineer — Scalable AI Infra & Deployment

Deloitte France; Kansas City (MO); On-site; USD 128,000 - 253,000; Full time

Job summary

Deloitte, via SFL Scientific, seeks a Senior AI Engineer to help design robust AI infrastructure and deployment services for novel ML applications. You’ll work with data scientists, ML engineers, and project managers to enable scalable data architectures and cloud/on‑prem solutions.

Requirements include 4+ years in data engineering/data science/software engineering/MLOps, strong cloud experience, and leadership skills.

Qualifications

• Bachelor’s degree in a STEM field (Computer Science, Engineering, Physics, etc.) or equivalent experience.
• 4+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and ML deployment.
• 4+ years of experience in designing cloud solutions and supporting production projects, including hands-on experience with AWS, Azure, or GCP.
• 4+ years of programming with Linux Shell/CLI, Python, SQL, PowerShell, etc.
• 2+ years leading technical delivery teams.
• 2+ years with DevOps and CI/CD tools: Puppet, Ansible, Chef, Airflow, Terraform, Jenkins.
• 2+ years with database development and ETL/ELT pipelines (relational, NoSQL, Neo4j).
• 2+ years with deployment/optimization: Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDS, Kubeflow, MLflow, Kafka.
• Live within commuting distance to Deloitte offices; travel ~10%
• Limited immigration sponsorship may be available
• Master’s degree preferred
• AWS/Azure Certifications preferred
• GPU computing / HPC experience a plus
• Wage range info provided by Deloitte: $128,000–$252,500 annually

Responsibilities

• Design, develop, and deploy architectures to support ML and automation apps.
• Use modern data architecture, data science engineering, data transformation, and data management.
• Lead scalable data architecture solutions for AI/GenAI use cases.
• Define schemas and data pipelines for scalable deployment in cloud or on-prem.
• Participate in architecture discussions to ensure security, scale, and availability.
• Adopt best engineering practices in automation and HPC/GenAI infrastructure.
• Lead proofs of concepts for new data/cloud tech.
• Mentor junior engineers and drive professional development.
• Lead projects or workstreams and manage multiple tasks.

Skills

Data engineering

Data science

Software engineering

MLOps

AI deployment

Cloud solutions

Project leadership

Communication

Education

Bachelor's degree in STEM

Master's degree (preferred)

Tools

AWS

Azure

GCP

Kubernetes

Docker

Jenkins

Airflow

Terraform

Puppet

Ansible

Chef

Kubeflow

Job description

Deloitte, via SFL Scientific, seeks a Senior AI Engineer to help design robust AI infrastructure and deployment services for novel ML applications. You’ll work with data scientists, ML engineers, and project managers to enable scalable data architectures and cloud/on‑prem solutions.

Requirements include 4+ years in data engineering/data science/software engineering/MLOps, strong cloud experience, and leadership skills.