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Ai Applications Engineer Jobs in Oregon (NOW HIRING)

Senior AI Identity Platform Engineer

OR · On-site +1

$104K - $143K/yr

Ability to obtain and maintain a Public Trust LTS is seeking a Senior AI Identity Platform Engineer to design and build the identity foundation that enables AI agents, enterprise applications, cloud ...

GTM AI Engineer

OR · On-site +1

As a GTM AI Engineer on the AI Operations team, you'll be at the forefront of our AI strategy ... Ensure agents and applications follow UX best practices, meet users where they already work, and ...

New

AI Engineer, Sr

Newberg, OR · On-site

$140 - $220/hr

Overview The AI Engineer, Sr plays a key role in building and scaling applied artificial ... JavaScript or TypeScript for integrating AI capabilities into web applications or internal tools

New

Principal Solutions Engineer

OR · On-site +1

$200K - $250K/yr

... and space constrained applications. EnCharge AI launched in 2022 and is led by veteran ... This is a senior technical role for an engineer who can bridge the gap between AI hardware ...

New

As a Principal Logic Design Engineer , you will play a pivotal role in the micro-architecture and ... and AI applications. This is a fast-growing market with high demand from tier-1 customers which ...

AI Engineer, Sr

Newberg, OR · On-site

$109K - $150K/yr

Overview The AI Engineer, Sr plays a key role in building and scaling applied artificial ... JavaScript or TypeScript for integrating AI capabilities into web applications or internal tools

AI Engineer, Sr

Newberg, OR

$109K - $150K/yr

Overview The AI Engineer, Sr plays a key role in building and scaling applied artificial ... JavaScript or TypeScript for integrating AI capabilities into web applications or internal tools

Ability to deploy applications or automations in a cloud environment and integrate AI APIs (Azure OpenAI, Azure Cognitive Services, etc.). DevOps Mindset: Experience with version control (git and ...

AI Engineer, Sr

Newberg, OR · On-site

$109K - $150K/yr

The AI Engineer, Sr will play a crucial role in developing and implementing applied artificial ... applications or internal tools • Bash or shell scripting for automation and deployment tasks • ...

Rapidly prototype full-stack, MVP-grade agents, applications, and workflows that demonstrate value ... You see AI tools as essential infrastructure for modern engineering. * You can rapidly prototype ...

AI & Automation Engineer

Portland, OR · On-site

$90K - $120K/yr

Ability to deploy applications or automations in a cloud environment and integrate AI APIs (Azure OpenAI, Azure Cognitive Services, etc.). * DevOps Mindset: Experience with version control (git and ...

We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that ... LLM applications using Claude-, GPT/Codex-, and Gemini-class models, and more implemented with ...

AI Platform Engineer

$125K - $165K/yr

AI Platform Engineer TELCOR Inc, a leading innovator in laboratory software, is looking for a AI ... This role will also develop frontend applications with ReactJS and TypeScript, as well as integrate ...

Forward Deployed AI Engineer

OR · On-site +1

$103K - $139K/yr

Experience working with AI / LLM technologies or AI-powered applications. Experience operating in client-facing engineering or consulting roles. Experience with cloud platforms such as AWS, Azure, or ...

As a Principal Logic Design Engineer , you will play a pivotal role in the micro-architecture and ... and AI applications. This is a fast-growing market with high demand from tier-1 customers which ...

Senior Software Engineer - Integrations - AI/ML

OR · On-site +1

$122K - $161K/yr

... millions of developers, data practitioners, and AI agents worldwide, from high-level data ... data applications that redefine how teams work with data. We collaborate closely with the open ...

Showing results 41-60

Ai Applications Engineer information

What is an AI applications engineer?

AI Applications Engineers are professionals who design, develop, and integrate artificial intelligence (AI) solutions into software applications to solve real-world problems. They work closely with data scientists, software engineers, and business stakeholders to build and deploy machine learning models, automate processes, and enhance user experiences. Their responsibilities often include selecting appropriate AI technologies, writing code, testing models, and optimizing performance. AI Applications Engineers play a key role in translating AI research and prototypes into scalable and maintainable products used in industries like healthcare, finance, retail, and more.

What are the key skills and qualifications needed to thrive as an AI applications engineer?

To thrive as an AI Applications Engineer, you need strong programming abilities (Python, Java, or C++), a solid understanding of machine learning algorithms, and a relevant degree in computer science or engineering. Familiarity with AI frameworks (such as TensorFlow or PyTorch), cloud platforms, and data processing tools is typically required, along with certifications in machine learning or AI. Excellent problem-solving, collaboration, and communication skills help you translate business needs into effective AI solutions and work efficiently with cross-functional teams. These skills are critical for building scalable, reliable AI systems that deliver tangible value to organizations.

How does an AI applications engineer typically collaborate with data scientists and software developers on project teams?

As an AI Applications Engineer, you will often serve as a bridge between data scientists, who build and optimize machine learning models, and software developers, who integrate these models into production systems. Collaboration usually involves translating model requirements into scalable application features, ensuring model outputs align with user needs, and troubleshooting technical challenges that arise during deployment. Regular meetings, code reviews, and shared documentation are common practices to keep everyone aligned and ensure seamless integration. This cross-functional teamwork enhances both the technical robustness and usability of AI-powered applications.

What is the difference between Ai Applications Engineer vs Data Scientist?

AspectAi Applications EngineerData Scientist
Required CredentialsBachelor's in CS, Engineering, or related; knowledge of AI/ML toolsBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops AI solutions, collaborates with engineering teamsAnalyzes data, builds models, interprets results
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, tech, research institutions

While both roles involve AI and data, Ai Applications Engineers focus on developing and deploying AI solutions in engineering contexts, whereas Data Scientists analyze data to extract insights. The roles often overlap but differ mainly in their primary focus and application environment.

What does an AI applications engineer do?

An AI applications engineer designs, develops, and implements artificial intelligence solutions to solve specific business problems. They work with machine learning models, data processing, and programming tools like Python or TensorFlow, often collaborating with data scientists and software developers to deploy AI systems effectively.

What are popular job titles related to Ai Applications Engineer jobs in Oregon?

For Ai Applications Engineer jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Ai Applications Engineer jobs in Oregon look for?

The top searched job categories for Ai Applications Engineer jobs in Oregon are:

What cities in Oregon are hiring for Ai Applications Engineer jobs?

Cities in Oregon with the most Ai Applications Engineer job openings:

Senior AI Identity Platform Engineer

LTS

OR • On-site, Remote

$104K - $143K/yr

Full-time

Posted 21 days ago


Job description

Location: United States - Remote
Clearance: Ability to obtain and maintain a Public Trust

LTS is seeking a Senior AI Identity Platform Engineer to design and build the identity foundation that enables AI agents, enterprise applications, cloud services, and users to interact securely and intelligently. You'll establish authentication, authorization, credential management, and identity services that allow autonomous AI systems to operate safely across enterprise environments.

The Agentic AI platform is designed to help engineers understand, analyze, and modernize one of the most consequential legacy software systems still operating today.

Our platform enables engineers to ask questions in plain English and receive explainable, verifiable answers traced directly back to decades of production source code. Rather than replacing engineers, we're building AI that accelerates engineering through transparency, traceability, and intelligent reasoning.

We're building an AI-native engineering platform supporting the modernization of mission-critical healthcare systems serving millions of Veterans nationwide.

The platform is designed for deployment across federal enterprise environments and is being engineered to align with FedRAMP security controls, Zero Trust principles, and federal compliance requirements.

The product has executive sponsorship, committed users, and a customer investing in long-term modernization. Our engineering team is intentionally small, giving every engineer meaningful ownership and direct influence over product direction.

We don't simply build AI-powered software, we build software with AI. This is not another chatbot.

Using LLMs, AI agents, secure identity architectures, and AI-assisted development is simply how we engineer.

What You'll Do:

Design AI Identity Architecture

  • Design identity services supporting autonomous and multi-agent AI systems.
  • Establish secure identities for AI agents, enterprise services, users, and external integrations.
  • Define identity lifecycles for AI agents, including provisioning, credential management, rotation, and decommissioning.
  • Build reusable identity capabilities that scale across the AI platform.

Authentication & Authorization

  • Design and implement modern authentication and authorization frameworks for AI agents and platform services.
  • Implement OAuth 2.0, OpenID Connect (OIDC), JWT, service principals, mutual TLS (mTLS), and delegated authorization models.
  • Apply least-privilege and Zero Trust principles throughout AI workflows.
  • Build fine-grained authorization models controlling AI access to enterprise data, APIs, tools, and services.

Enterprise Identity Integration

  • Integrate AI platforms with enterprise identity providers such as Microsoft Entra ID, Okta, Active Directory, and other IAM solutions.
  • Enable secure identity federation across cloud and on-premises environments.
  • Design secure service-to-service authentication supporting distributed AI architectures.
  • Collaborate with enterprise security teams to align AI identity with organizational security standards.

Secure Agent & Tool Access

  • Design secure frameworks governing how AI agents discover, authenticate to, and invoke enterprise APIs, databases, and external tools.
  • Build authorization models controlling agent capabilities and delegated permissions.
  • Protect sensitive enterprise resources through policy-driven access controls.
  • Implement secure credential handling and secrets management across AI workflows.

Platform Engineering

  • Develop reusable identity services, SDKs, APIs, and libraries supporting secure AI application development.
  • Automate identity provisioning, credential lifecycle management, and authorization policies.
  • Improve developer productivity through standardized identity services and secure engineering patterns.
  • Partner with platform engineers to integrate identity services into the AI platform architecture.

Governance & Auditability

  • Ensure every AI action is authenticated, authorized, attributable, and auditable.
  • Implement identity-aware logging, traceability, and policy enforcement.
  • Support compliance and governance requirements for highly regulated environments.
  • Partner closely with AI Security Engineers to establish secure-by-design AI development practices.

What We're Looking For:

  • Bachelor's degree in Computer Science, Software Engineering, Cybersecurity, Information Systems, or a related technical discipline (or equivalent professional experience).
  • 7+ years of software engineering, platform engineering, identity engineering, or cloud security experience.
  • Experience designing authentication and authorization architectures for enterprise applications.
  • Strong knowledge of OAuth 2.0, OpenID Connect (OIDC), JWT, SAML, PKI, and modern identity protocols.
  • Experience integrating enterprise identity providers such as Microsoft Entra ID, Okta, Active Directory, or similar IAM platforms.
  • Experience building secure REST APIs, microservices, and distributed systems.
  • Knowledge of Zero Trust Architecture, RBAC, ABAC, delegated authorization, and identity federation.
  • Experience with cloud platforms (Azure, AWS, or Google Cloud).
  • Strong programming skills in Python plus experience with Go, Java, or TypeScript.
  • Excellent communication, analytical, and problem-solving skills.
  • Experience designing secure systems that enable innovation rather than restrict it.
  • Expertise in identity and access management.
  • Hands-on experience with cloud-native architecture and modern authentication frameworks.
  • Strong ability to stay current with emerging AI technologies and evolving identity standards.
  • Ability to collaborate effectively across software engineering, security, and AI disciplines.
  • Willing and able to take ownership of difficult technical challenges and build elegant, innovative solutions.

Nice to Have: 

  • Experience developing AI platforms, Agentic AI systems, or Large Language Model (LLM) applications.
  • Experience securing Retrieval-Augmented Generation (RAG) systems and AI tool integrations.
  • Familiarity with Model Context Protocol (MCP) and secure AI tool invocation.
  • Experience with HashiCorp Vault, Azure Key Vault, AWS Secrets Manager, or similar secrets management platforms.
  • Experience implementing identity services in Kubernetes and cloud-native environments.
  • Experience with AI governance, Responsible AI, or AI platform security.
  • Familiarity with LangGraph, LangChain, CrewAI, Semantic Kernel, AutoGen, or similar AI orchestration frameworks.
  • Experience supporting Federal Government or healthcare environments.
  • Identity or cloud certifications such as Microsoft Identity and Access Administrator, CISSP, Security+, CCSP, or cloud security certifications are a plus.

What's In It for You?

  • The Opportunity to support high-visibility federal missions
  • A culture that values innovation, growth, and collaboration
  • Access to cutting-edge tools and technologies
  • Comprehensive benefits for you and your family
  • A career path that rewards ambition and performance

If you're ready to push boundaries, sharpen your skills, and join a team that is passionate about building what's next, we'd love to meet you. Apply today and let's build a future together!