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Backend Ai Engineer Jobs in Remote, OR (NOW HIRING)

Sara Software Systems

AI Engineer

OR · Remote

Develop APIs and backend services that connect front-end applications with AI/ML models and data pipelines * Build, evaluate, and optimize LLM-based solutions including prompt engineering, RAG ...

Sara Software Systems

AI Engineer

OR · Remote

Develop APIs and backend services that connect front-end applications with AI/ML models and data pipelines * Build, evaluate, and optimize LLM-based solutions including prompt engineering, RAG ...

Team8

Charm Security-Forward Deployed AI Engineer

OR · On-site +1

Strong software engineering skills with experience building integrations, APIs, automation, or backend systems * Experience working with AI systems, LLMs, AI agents, or agentic workflows * Experience ...

Anytime AI

Infrastructure Engineer

OR · Remote

$100K - $200K/yr

Position Overview As an Infrastructure Engineer, you will play a pivotal role in building and ... Hands-on experience participating in the architecture or backend service development of Agentic AI ...

Avaya

Senior Front End Engineer - Avaya Infinity Platform

OR · Remote

$125K - $172K/yr

... AI-assisted development tools thoughtfully - using them to accelerate delivery while applying ... backend fluency with Node.js microservices, message brokers (Kafka), caching layers (Redis), or ...

All JobsBackend Ai Engineer JobsBackend Ai Engineer Jobs in Remote, OR

Backend Ai Engineer information

See Remote, OR salary details

$60.4K

$147.5K

$198.8K

How much do backend ai engineer jobs pay per year?

As of Aug 18, 2026, the average yearly pay for backend ai engineer in Remote, OR is $147,516.00, according to ZipRecruiter salary data. Most workers in this role earn between $123,900.00 and $171,800.00 per year, depending on experience, location, and employer.

What is a Backend AI Engineer?

A Backend AI Engineer is a software engineer who specializes in building and maintaining the server-side infrastructure for artificial intelligence applications. Their work involves designing APIs, integrating machine learning models, managing databases, and ensuring efficient data flow between systems. They collaborate with data scientists and frontend developers to deploy AI models at scale and make them accessible through robust backend services. Key skills for this role include programming (often in Python, Java, or similar languages), cloud computing, and knowledge of AI frameworks.

What are the key skills and qualifications needed to thrive as a backend AI engineer?

To thrive as a Backend AI Engineer, you need strong programming skills (especially in Python or Java), a deep understanding of algorithms and data structures, and a background in computer science or related fields. Familiarity with AI/ML frameworks (like TensorFlow or PyTorch), RESTful APIs, databases, and cloud platforms is typically expected, along with relevant certifications. Exceptional problem-solving abilities, teamwork, and effective communication are soft skills that distinguish top performers. These competencies are crucial for designing robust, scalable AI solutions that integrate seamlessly with backend systems and drive innovation.

What are some common challenges backend AI engineers face when deploying machine learning models to production?

Backend AI Engineers often encounter challenges such as ensuring model scalability, maintaining low latency, and handling diverse data inputs during deployment. Integrating models into existing backend systems can also require careful consideration of APIs, security, and resource management. Additionally, monitoring model performance and updating models with new data are ongoing responsibilities that require close collaboration with data scientists, DevOps, and product teams.

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

AspectBackend Ai EngineerData Scientist
Required CredentialsBachelor's in CS, AI, or related field; knowledge of programming, AI frameworksBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops AI models, integrates AI into backend systems, collaborates with software teamsAnalyzes data, builds models, interprets data insights, collaborates with business teams
Industry UsageTech companies, AI startups, software firmsResearch institutions, tech companies, finance, healthcare
Common Search/ComparisonYesYes

While both roles involve working with AI and data, Backend Ai Engineers focus on integrating AI models into backend systems and developing scalable AI solutions. Data Scientists primarily analyze data, build predictive models, and generate insights. The roles often overlap in skills and tools but differ in their core focus—system integration versus data analysis.

What are popular job titles related to Backend Ai Engineer jobs in Remote, OR?

For Backend Ai Engineer jobs in Remote, OR, the most frequently searched job titles are:

What job categories do people searching Backend Ai Engineer jobs in Remote, OR look for?

The top searched job categories for Backend Ai Engineer jobs in Remote, OR are:

Backend Ai Engineer jobs near you

AI Engineer

Sara Software Systems

OR • Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 28 days ago

Job description

We are seeking an AI Engineer who is, first and foremost, a strong software engineer. In this role, you will design, build, and ship AI-powered features end to end, from integrating large language models and machine learning services into our products, to developing the front-end applications that put those capabilities in users' hands. You will work across the stack, with a strong emphasis on front-end development and cloud-native engineering on Google Cloud Platform (GCP). 

Responsibilities 

  • Design, develop, and deploy AI-powered applications and features, integrating LLMs and ML models into production software 
  • Build and maintain responsive, high-quality front-end applications using modern JavaScript frameworks (React, Angular, or Vue) 
  • Develop APIs and backend services that connect front-end applications with AI/ML models and data pipelines 
  • Build, evaluate, and optimize LLM-based solutions including prompt engineering, RAG (Retrieval-Augmented Generation) pipelines, embeddings, and vector search 
  • Architect, deploy, and manage applications and AI workloads on Google Cloud Platform (Vertex AI, Cloud Run, Cloud Functions, BigQuery, GKE) 
  • Fine-tune and integrate models from providers such as OpenAI, Anthropic, and Google, as well as open-source models (Hugging Face, LLaMA, etc.) 
  • Implement MLOps/LLMOps best practices: CI/CD pipelines, model monitoring, evaluation, and versioning 
  • Write clean, well-tested, maintainable code and participate in code reviews 
  • Collaborate with product managers, designers, and stakeholders to translate business requirements into technical solutions 
  • Stay current with the rapidly evolving AI/ML landscape and recommend new tools and approaches 

Required Qualifications 

  • Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent practical experience) 
  • 3+ years of professional software engineering experience 
  • Strong proficiency in Python and JavaScript/TypeScript 
  • Hands-on experience building front-end applications with React, Angular, or similar frameworks (HTML, CSS, modern UI patterns) 
  • Experience developing and deploying applications on Google Cloud Platform 
  • Practical experience integrating LLM APIs (OpenAI, Anthropic Claude, Google Gemini) into applications 
  • Experience with RESTful APIs, microservices, and modern software architecture 
  • Familiarity with vector databases (Pinecone, Weaviate, pgvector, or similar) and RAG architectures 
  • Solid understanding of Git, CI/CD, containerization (Docker), and agile development practices 
  • Strong problem-solving skills and ability to work independently and within a team 

Preferred Qualifications 

  • Experience with Vertex AI, LangChain, LlamaIndex, or similar AI application frameworks 
  • Experience with agentic AI workflows, function/tool calling, and multi-agent systems 
  • Knowledge of ML fundamentals: model training, fine-tuning, and evaluation (PyTorch or TensorFlow) 
  • Experience with Kubernetes (GKE) and infrastructure-as-code (Terraform) 
  • Experience with SQL/NoSQL databases and data pipelines (BigQuery, Dataflow) 
  • GCP certifications (e.g., Professional Machine Learning Engineer, Professional Cloud Developer) 
  • Experience shipping user-facing AI products from concept to production 

Company Description

Sara Software Systems, LLC founded in July 2004 is a small, woman, minority owned and economically disadvantaged 8(a) business as approved by the Small Business Administration (SBA). Owned and managed by experienced IT professionals, we bring a realistic and knowledgeable approach with 15 years of technical excellence to solve complex federal and commercial IT challenges, transform how organizations operate, and protect our Customer's critical infrastructure.
Sara Software Systems, LLC is a process-driven and quality-focused company and we are appraised at Maturity Level (ML) 3 by the CMMI Institute for both DEV + SVC. Our CMMI DEV ML3 appraisal was specifically focused on Agile and DevSecOps. We are International Standards of Organization (ISO) 9001:2015, ISO 20000-1:2011 and ISO 27001:2013-certified.

Sara Software Systems, LLC is a leading technology Services provider with focus in Application Development and Modernization, Agile Transformations, Program Management , Information Technology , Software development, Cybersecurity, IT infrastructure, Business Process Reengineering and Service Desk services for Federal Agencies and commercial organizations. We serve the business needs of our customers by providing strategy, program management, architecture, and sustainment of information technology solutions both in traditional waterfall and agile methodologies that transform ideas to value.