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Large Language Model Llm Jobs in Oregon (NOW HIRING)

LTS

AI Platform and Harness Engineer

OR · On-site +1

... Large Language Model (LLM), or machine learning applications. * Strong programming experience in Python. * Experience developing APIs, backend services, and distributed systems. * Experience with ...

Smarsh

Lead Data Scientist

OR · On-site +1

Summary As a Lead Data Scientist (NLP & Financial Compliance) at Smarsh , you will spearhead the development of state-of-the-art natural language processing (NLP) and large language model (LLM ...

Intel

Senior AI / Data Science Engineer

Hillsboro, OR

$115K - $156K/yr

Develop and deploy Large Language Model (LLM) and Generative AI applications that improve engineering productivity, accelerate troubleshooting, and enhance knowledge discovery. * Analyze large-scale ...

BetterHelp

Machine Learning Engineer

OR · On-site +1

This role will focus on Natural Language Processing (NLP), Large Language Models (LLMs), evaluation ... Improve latency, scalability, and operational efficiency of LLM-powered applications. * Partner ...

WEKA

Tech Lead - AI Inference

OR · On-site +1

... Large Language Model (LLM) serving. The ideal candidate combines deep technical expertise in inference and scale with the leadership maturity to mentor, motivate, and develop engineers in the ...

Relativity

Software Engineer

Portland, OR · On-site

Experience working with large language model (LLM) APIs or generative AI systems * Experience designing and building scalable systems in Azure or other cloud platforms * Experience with Kubernetes ...

Bishop Fox

Senior AI/LLM Penetration Tester

OR · On-site +1

We are now hiring a Senior AI/LLM Security Consultant to help clients stay ahead of emerging AI threats by conducting cutting-edge security assessments of large language models, AI agents, and AI ...

Liftoff

Security Engineer, Detection & Response

OR · On-site +1

Hands-on experience with an AI-augmented SOC platform (Prophet Security, Dropzone AI, or equivalent), or with building large language model (LLM) augmented investigation and runbook tooling.

Nvidia

Senior Software Engineer, DGX Cloud AI Infrastructure

OR · On-site +1

$122K - $161K/yr

... large language model workloads. We are looking for a Senior Software Engineer to lead the bring-up ... Analyze scaling efficiency for distributed LLM workloads using data, tensor, pipeline, and expert ...

Nvidia

Software Engineer, DGX Cloud AI Infrastructure

OR · On-site +1

$172K - $204K/yr

... large language model workloads. We are looking for a Software Engineer focused on bring-up, triage ... In this role you will help bring up, benchmark, and debug distributed LLM workloads on multi-GPU ...

LTS

Lead AI Architect/Strategist

OR · On-site +1

LLM-based applications, Agentic AI workflows, AI copilots and automation solutions, knowledge ... Proven experience with Generative AI, Large Language Models (LLMs), and AI application ...

Nvidia

Senior Software Engineer, Matrix Multiplication

OR · On-site +1

$122K - $161K/yr

... new LLM inference runtimes components, and kernel code generators to accelerate large language models, agents, and other high-impact AI workloads. What you'll be doing: * Innovating and developing ...

Deloitte

Customer Deployment Specialist

Portland, OR · On-site

Experience with artificial intelligence/large language model platform features, including Skills, Model Context Protocol (MCP), Plugins, or partner-led delivery models involving systems integrators ...

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All JobsLarge Language Model Llm JobsLarge Language Model Llm Jobs in Oregon

Large Language Model Llm information

What is a large language model llm?

A Large Language Model (LLM) job typically involves working with advanced AI models designed to understand and generate human-like text. Roles in this field may include research, data engineering, model fine-tuning, prompt engineering, or application development. Professionals in LLM jobs often work with machine learning algorithms, natural language processing (NLP), and large-scale datasets to enhance AI capabilities. These roles are common in AI-driven industries, including tech companies, research institutions, and startups. Strong programming skills, knowledge of deep learning frameworks, and expertise in NLP are often required.

What are some common challenges faced by large language model llm engineers in their day-to-day work?

LLM Engineers often encounter challenges related to scaling models efficiently, optimizing performance on large and complex datasets, and ensuring the responsible use of AI technologies. Balancing the trade-offs between model accuracy, speed, and ethical considerations can be demanding, especially as real-world applications often require rapid iterations and rigorous testing. Additionally, staying updated with the latest research advancements and integrating new methods into production systems is an ongoing responsibility. Many engineers tackle these challenges by working closely with data scientists, researchers, and product teams in collaborative, agile environments.

What are the key skills and qualifications needed to thrive in the large language model llm position?

Excelling in the role of a Large Language Model (LLM) Engineer requires strong expertise in natural language processing, machine learning, and computer programming, often supported by an advanced degree in computer science or a related field. Familiarity with industry-standard frameworks like PyTorch or TensorFlow, as well as experience with cloud computing platforms and large-scale data management, is highly valued. Communication, creativity, and problem-solving are essential soft skills to effectively collaborate with cross-functional teams and innovate solutions. These skills ensure the development, deployment, and refinement of powerful language models that can address diverse business needs and technical challenges.

What jobs can I do with large language model?

Large Language Models (LLMs) are used in roles such as AI research scientist, NLP engineer, data scientist, and machine learning engineer. These jobs involve developing, fine-tuning, and deploying LLMs for applications like chatbots, content generation, and language understanding, often requiring skills in programming, data analysis, and deep learning frameworks.

What are the most commonly searched types of Large Language Model Llm jobs in Oregon?

The most popular types of Large Language Model Llm jobs in Oregon are:

What are popular job titles related to Large Language Model Llm jobs in Oregon?

For Large Language Model Llm jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Large Language Model Llm jobs in Oregon look for?

The top searched job categories for Large Language Model Llm jobs in Oregon are:

Large Language Model Llm jobs near you
Infographic showing various Large Language Model Llm job openings in Oregon as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution.

AI Platform and Harness Engineer

OR • On-site, Remote

LTS
See more jobs at LTSexternal

Full-time

Posted 27 days ago

Job description

LTS is seeking an AI Platform and Harness Engineer to develop and maintain the infrastructure, tooling, and evaluation frameworks that power enterprise AI solutions. This role is responsible for building the AI platform and reusable "AI harnesses" that enable Large Language Models (LLMs), AI agents, Retrieval-Augmented Generation (RAG), and Generative AI applications to be securely developed, tested, evaluated, monitored, and deployed at scale.

The ideal candidate has experience with AI platforms, LLMOps, software engineering, cloud-native technologies, and backend systems, along with a passion for building reliable, observable, and production-ready AI solutions. You will work closely with AI architects, software engineers, data scientists, and product teams to ensure AI solutions are scalable, secure, cost-effective, and continuously improving.

What You'll Do:

  • Design, build, and maintain enterprise AI platform capabilities supporting Large Language Models (LLMs), AI agents, RAG, and Generative AI applications.
  • Develop reusable AI harnesses to automate testing, prompt evaluation, model benchmarking, regression testing, and quality assurance.
  • Build AI evaluation frameworks to measure model accuracy, retrieval quality, hallucination detection, latency, throughput, cost, and overall application performance.
  • Implement observability and monitoring solutions for AI applications, including telemetry, tracing, logging, dashboards, and operational metrics.
  • Build and maintain LLMOps pipelines supporting model deployment, versioning, evaluation, experimentation, rollback, and continuous improvement.
  • Design automated workflows for prompt testing, retrieval evaluation, AI system validation, and performance benchmarking.
  • Develop internal tools for prompt management, model experimentation, AI performance optimization, and developer productivity.
  • Build scalable backend services and APIs supporting AI platforms and enterprise AI integrations.
  • Collaborate with AI architects and engineering teams to integrate LLMs, RAG pipelines, vector databases, and agentic AI solutions into enterprise applications.
  • Support deployment of AI services across AWS, Azure, or Google Cloud using containerized and cloud-native architectures.
  • Implement CI/CD pipelines and infrastructure automation supporting enterprise AI development and deployment.
  • Apply security, governance, and Responsible AI controls throughout the AI development lifecycle.
  • Evaluate emerging AI frameworks, LLMOps technologies, evaluation methodologies, and automation tools to improve engineering productivity.
  • Troubleshoot production AI issues and continuously improve platform reliability, scalability, security, and user experience.
  • Document engineering standards, AI platform architecture, evaluation methodologies, and operational best practices.

What We're Looking For:

  • Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related technical field.
  • 5+ years of experience in software engineering, platform engineering, backend engineering, DevOps, cloud engineering, or infrastructure engineering.
  • 2+ years building or supporting Generative AI, Large Language Model (LLM), or machine learning applications.
  • Strong programming experience in Python.
  • Experience developing APIs, backend services, and distributed systems.
  • Experience with cloud platforms including AWS, Azure, or Google Cloud Platform.
  • Experience deploying applications using Docker and Kubernetes.
  • Experience working with Git, CI/CD pipelines, Infrastructure as Code (IaC), and infrastructure automation.
  • Strong understanding of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Prompt engineering, Embeddings, Vector databases, AI agents and agentic workflows
  • Familiarity with AI evaluation techniques, automated testing, benchmarking, regression testing, and model validation.
  • Experience building scalable, production-grade software platforms.
  • Strong problem-solving, debugging, and performance optimization skills.

Nice to Have:

  • Experience with AI orchestration frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or AutoGen.
  • Experience implementing LLMOps or MLOps platforms and deployment pipelines.
  • Experience with AI observability tools such as LangSmith, OpenTelemetry, Prometheus, Grafana, Evidently AI, or Arize AI.
  • Experience with vector databases including Pinecone, Qdrant, Weaviate, Azure AI Search, or pgvector.
  • Experience with OpenAI, Azure OpenAI, AWS Bedrock, Anthropic Claude, Google Vertex AI, or similar enterprise AI platforms.
  • Experience implementing Responsible AI, AI governance, model security, and AI safety best practices.
  • Experience supporting Federal Government or other regulated environments.
  • Experience evaluating AI systems for quality, reliability, accuracy, explainability, latency, and cost optimization.
  • Familiarity with healthcare, enterprise modernization, or mission-critical systems.

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!

Apply