AI Platform Engineer

DPR Construction

. Build and refine end-to-end generative AI solutions aligned with business objectives .

Posted 10/5/2026full-timeUnited StatesJuniorMid-LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and refining generative AI solutions, translating business requirements into technical implementations, and ensuring model scalability, reliability, and security. Proficient in Python for data preparation and analysis, with a strong focus on CI/CD pipelines and containerized ML workloads.

Highest-signal resume keywords

Generative AI SolutionsPython Data PreparationModel ScalabilityCI/CD PipelinesContainerized ML Workloads

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningAI DevelopmentData ScienceModel DesignData TransformationObservability PracticesLLM/AI GatewaysCost Tracking ControlsRate-LimitingSecurity Guardrails

Soft Skills

CollaborationCommunication

Tools & Technologies

CI/CDContainerizationInfrastructure ManagementAI AgentsML Workflows

Industry Keywords

Data ScienceAI IntegrationTechnical ImplementationBusiness ObjectivesInnovation Initiatives

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Build and refine end-to-end generative AI solutions aligned with business objectives
Translate business requirements into AI model designs and technical implementation plans
Implement best practices for model scalability, reliability, security, and maintainability
Prepare, transform, and analyze data using Python and related technologies
Collaborate with cross-functional stakeholders and communicate findings to technical and non-technical audiences
Support AI integration initiatives aligned with the enterprise roadmap
Evaluate emerging AI capabilities and contribute to innovation initiatives
Standardize observability practices across AI/ML and data teams, including logging, metrics, tracing, and model/AI agent performance
Implement and maintain LLM/AI gateways, cost tracking controls, rate-limiting, and security guardrails
Build a secure, self-service framework for engineering teams to deploy AI agents, models, and services independently
Extend CI/CD pipelines for code-first infrastructure management and ML workflows
Design and deploy containerized ML workloads in partnership with Infrastructure Engineering on cluster provisioning, scaling, and tuning

Requirements

What you’ll need

Bachelor’s degree in computer science, data science, engineering, or a related field, or equivalent experience required
2–4 years of experience in machine learning, AI development, data science, or related field required
Experience with Python and related technologies for data preparation, transformation, and analysis
Knowledge of generative AI solutions, AI model design, and deployment strategies
Knowledge of model scalability, reliability, security, and maintainability
Knowledge of logging, metrics, tracing, and model/AI agent performance observability
Experience implementing LLM/AI gateways, cost tracking controls, rate-limiting, and security guardrails
Experience building self-service frameworks for deploying AI agents, models, and services
Experience with CI/CD pipelines, code-first infrastructure management, and ML workflows
Experience designing and deploying containerized ML workloads
Ability to collaborate with cross-functional stakeholders and communicate findings to technical and non-technical audiences

Benefits

Comp & perks

Private, employee-owned company
Opportunity to try new things, explore paths and shape your future
Employee recognition as a great place to work