AI Platform Engineer - Cloud-Native, Hybrid

AVEVA; Lake Forest (CA); Hybrid; USD 103,500 - 172,500; Full time

Benefits offered by this job

Flex work hours

PTO 20–25 days

Volunteer days

Parental leave

Well-being support

Medical insurance

Dental insurance

Vision insurance

401K

Job summary

AVEVA, Lake Forest, CA, is seeking an AI Software Engineer to design, develop, and scale AI-enabled platform services and public APIs. You will join a Scrum team, focusing on secure, production-grade AI capabilities and rapid prototyping in a hybrid work environment.

The role emphasizes building scalable cloud-native services on Microsoft Azure, API development, and collaboration across global R&D teams. Strong experience with LLMs, RAG, and AI tooling is essential for success.

Qualifications

• Experience with LLMs and trade-offs between performance and cost.
• Familiarity with MCP and A2A standards.
• Strong Python and AI tooling experience (PyTorch/TensorFlow).

Responsibilities

• Collaborate with multiple teams to deploy AI solutions including model deployment and tooling.
• Build scalable, cloud-native AI services on Azure with high performance.
• Create secure, well-documented public APIs and SDKs for internal and external developers.
• Work across data pipelines, orchestration, and service APIs to deliver end-to-end solutions.
• Embed robust security controls to protect data and access to AI services.

Skills

LLMs

RAG

prompt engineering

tool calling

Agent orchestration

Python

PyTorch

TensorFlow

RESTful API design

API security

Cloud-native services

Azure Functions

AKS

API Management

Agile teams

Tools

Azure Functions

AKS

API Management

Job description

AVEVA, Lake Forest, CA, is seeking an AI Software Engineer to design, develop, and scale AI-enabled platform services and public APIs. You will join a Scrum team, focusing on secure, production-grade AI capabilities and rapid prototyping in a hybrid work environment.

The role emphasizes building scalable cloud-native services on Microsoft Azure, API development, and collaboration across global R&D teams. Strong experience with LLMs, RAG, and AI tooling is essential for success.