AI Platform Engineer

The AI Platform Engineer is responsible for designing, building, and

operationalizing the organization's AI platform capabilities across cloud

infrastructure, enterprise systems, and customer-facing digital platforms. This

role serves as a technical leader within the IT organization and partners

closely with Digital Development, Enterprise Systems, Operations, and business

stakeholders to create scalable, secure, and reusable AI-enabled platform

services that enhance both internal operations and external digital user

experiences.

A core function of this role is establishing and evolving the organization's AI

Service Layer and supporting platform architecture including AI orchestration

services, reusable APIs, customer-specific deployment models, and scalable

cloud-native platform services—while ensuring scalability, maintainability,

operational reliability, and security across environments.

This role bridges AI engineering, cloud architecture, SaaS platform engineering,

DevOps collaboration, and enterprise data enablement to ensure AI capabilities

can be consistently deployed, integrated, governed, and scaled across both

enterprise operations and customer-facing digital platform experiences. This is

a REMOTE position.

RESPONSIBILITIES

AI Platform Architecture & Engineering: Design, develop, and maintain reusable

AI platform services and infrastructure components that support enterprise AI

initiatives and customer-facing digital platforms, including AI APIs,

orchestration services, retrieval-augmented generation (RAG) pipelines, prompt

management, vector search capabilities, model integration frameworks, and

reusable backend AI services.

Digital Platform AI Enablement: Design and implement AI capabilities that

enhance customer-facing digital platforms and SaaS applications, including

intelligent workflows, conversational interfaces, recommendation systems,

predictive insights, automation services, and AI-assisted user experiences.

Partner closely with frontend, backend, and UX teams to ensure AI capabilities

are seamlessly integrated into unified digital platform experiences.

AI Service Layer Development: Build and maintain a centralized AI Service Layer

that standardizes how enterprise systems, digital platforms, and SaaS

applications consume AI capabilities, ensuring reusable patterns for model

access, prompt orchestration, logging, security, governance, and scalable AI

integration across customer-facing and internal solutions.

Enterprise Data & AI Enablement: Partner closely with Data Integrations

Engineering and Enterprise Systems teams to ensure enterprise data assets are

accessible, structured, secure, normalized, and optimized for AI and analytics

workloads across both internal and customer-facing systems.

SaaS Platform Architecture & Deployment Support: Support scalable multi-tenant

and customer-specific SaaS deployment models, including customer environment

provisioning standards, AI service deployment architecture, database isolation

strategies, deployment automation, and platform scalability best practices.

Technical Leadership & Cross-Functional Collaboration: Collaborate closely with

DevOps, Backend Engineering, Data Integrations, Enterprise Systems, Frontend

Development, and UI/UX teams to define scalable AI integration standards,

reusable AI-enabled development patterns, and AI platform best practices across

the organization. Partner with business departments including Operations, Sales,

R&D, and other functional teams to identify opportunities for AI-enabled process

improvement, intelligent automation, predictive insights, and enhanced digital

platform capabilities that align with organizational objectives and operational

needs.

QUALIFICATIONS

The successful candidate will have significant experience designing and

operationalizing scalable cloud-based AI and platform engineering solutions,

with the ability to bridge AI systems, cloud infrastructure, SaaS platform

architecture, enterprise data integration, and customer-facing digital

experiences.

Specifically, the candidate should have:

* Bachelor's degree in Computer Science, Software Engineering, Artificial

Intelligence, Data Engineering, or related field.

* 5+ years of experience in AI engineering, machine learning engineering, AI

platform development, or related technical roles.

* Demonstrated experience building and deploying AI-enabled applications, AI

services, or customer-facing AI capabilities in production environments.

* Strong proficiency in Python, SQL, REST APIs, and AI service development.

* Experience designing and deploying AI/ML services using Azure, Anthropic,

vector databases, or related AI tooling.

* Experience integrating AI capabilities into customer-facing web applications,

SaaS products, or digital platform experiences.

* Familiarity with scalable SaaS application architectures, API integration

patterns, and AI orchestration workflows.

* Familiarity with relational databases, secure data access concepts, and

customer-aware data architectures.

* Strong analytical, systems-thinking, and problem-solving capabilities.

* Ability to clearly communicate technical concepts and AI solution designs to

both technical and non-technical stakeholders.

* Ability to work independently and collaboratively within cross-functional

teams including Backend Engineering, Frontend Development, DevOps, Data

Integrations, and UI/UX.

* Willingness to travel occasionally (approximately 10%).

PREFERRED

* Master's degree in Computer Science, Artificial Intelligence, Data

Engineering, or related field.

* Experience building enterprise AI service layers, AI orchestration platforms,

or reusable AI-enabled application services.

* Experience integrating AI capabilities into customer-facing SaaS applications

or digital platform experiences.

* Experience with Azure AI Services, Azure Functions, Azure SQL, Azure Data

Factory, Event Grid, Service Bus, or related Azure platform services.

* Experience working within scalable SaaS application environments and

customer-aware deployment models.

* Experience with observability, monitoring, logging, and operational support

for AI-enabled services.

* Experience implementing secure AI governance, model access controls, and

operational AI best practices.

* Experience mentoring engineers or providing technical leadership across

cross-functional development teams.

* Relevant Azure, AI, or cloud-related certifications.

USALCO is an equal opportunity/affirmative action employer. All qualified

applicants will receive consideration for employment without regard to sex,

gender identity, sexual orientation, race, color, religion, national origin,

disability, protected veteran status, age, or any other characteristic protected

by law. As a general policy, USALCO does not offer employment visa sponsorships

upon hire or in the future.

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