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Genai Developer Jobs in Remote, OR (NOW HIRING)

Atos

Apps AI Solution Architect AMS

OR · Remote

$59 - $77.75/hr

Required Skills & Experience * 10-15 years of experience in Application Architecture, Engineering, or Digital Transformation, with at least 2-3 years in AI/ML or GenAI implementation. * Strong ...

Atos

Apps AI Solution Architect AMS

OR · On-site +1

$59 - $77.75/hr

Required Skills & Experience * 10-15 years of experience in Application Architecture, Engineering, or Digital Transformation, with at least 2-3 years in AI/ML or GenAI implementation. * Strong ...

Atos

Head of AI

OR · On-site +1

Build and maintain a 12-24 month capability roadmap across GenAI, Agentic AI, applied ML, AI engineering, MLOps, and AI governance. * Identify strategic bets (industries, partnerships, platforms) and ...

Atos

Head of AI

OR · On-site +1

Build and maintain a 12-24 month capability roadmap across GenAI, Agentic AI, applied ML, AI engineering, MLOps, and AI governance. * Identify strategic bets (industries, partnerships, platforms) and ...

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Genai Developer information

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$17

$52

$81

How much do genai developer jobs pay per hour?

As of May 29, 2026, the average hourly pay for genai developer in Remote, OR is $52.79, according to ZipRecruiter salary data. Most workers in this role earn between $40.34 and $64.62 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a GenAI Developer, and why are they important?

To thrive as a GenAI Developer, you need a strong background in machine learning, deep learning frameworks (like TensorFlow or PyTorch), and programming languages such as Python, often supported by a degree in computer science or a related field. Familiarity with cloud platforms (AWS, Azure, GCP), APIs, and prompt engineering, as well as certifications in AI or ML, are typically used in this role. Creativity, problem-solving, and effective communication set outstanding GenAI Developers apart. These skills are crucial for building, optimizing, and deploying powerful generative AI models that address complex business challenges.

What are some common challenges GenAI Developers face when integrating generative AI models into existing products?

GenAI Developers often encounter challenges related to model deployment, scalability, and ensuring data privacy when integrating generative AI models into established products. Balancing the computational requirements of large AI models with real-time application demands can be complex, and optimizing inference speed without sacrificing model quality is a key consideration. Additionally, collaborating closely with product managers, data scientists, and DevOps teams is essential to align AI outputs with business goals and maintain robust, ethical AI practices.

What are GenAI Developers?

GenAI Developers are professionals who design, build, and optimize applications using generative artificial intelligence technologies. They work with models such as GPT, DALL-E, or Stable Diffusion to create tools for generating text, images, code, and other content. These developers need strong programming skills, a solid understanding of machine learning, and experience working with AI frameworks and APIs. Their responsibilities often include training custom models, integrating AI into products, and ensuring ethical use of generative AI solutions.

What is the difference between Genai Developer vs Machine Learning Engineer?

AspectGenai DeveloperMachine Learning Engineer
Required CredentialsBachelor's in CS, AI, or related; experience with NLP and AI frameworksBachelor's or higher in CS, Data Science, or related; strong programming and ML skills
Work EnvironmentDevelops AI models focused on generative AI, often in AI startups or tech companiesBuilds and deploys ML models across various industries, including tech, finance, healthcare
Employer & Industry UsagePrimarily in AI-focused companies, research labs, and tech firmsWidely used across industries like tech, finance, healthcare, and retail

While both roles involve AI and machine learning, Genai Developers specialize in creating generative AI models like chatbots and content generators, whereas Machine Learning Engineers develop a broader range of ML models for various applications. The roles overlap in skills and tools but differ in focus and industry applications.

What are popular job titles related to Genai Developer jobs in Remote, OR? For Genai Developer jobs in Remote, OR, the most frequently searched job titles are:
What job categories do people searching Genai Developer jobs in Remote, OR look for? The top searched job categories for Genai Developer jobs in Remote, OR are:
Genai Developer jobs near you
Infographic showing various Genai Developer job openings in Remote, OR as of May 2026, with employment types broken down into 86% Full Time, 5% Part Time, 2% Temporary, and 7% Contract. Highlights an 72% Physical, 1% Hybrid, and 27% Remote job distribution, with an average salary of $109,796 per year, or $52.8 per hour.

Apps AI Solution Architect AMS

Atos

Remote

$59 - $77.75/hr

Other

Posted 5 days ago

Job description

About Atos Group

Atos Group is a global leader in digital transformation with c. 63,000 employees and annual revenue of c. 8 billion, operating in 61 countries under two brands - Atos for services and Eviden for products. European number one in cybersecurity, cloud and high performance computing, Atos Group is committed to a secure and decarbonized future and provides tailored AI-powered, end-to-end solutions for all industries. Atos Group is the brand under which Atos SE (Societas Europaea) operates. Atos SE is listed on Euronext Paris.

The purpose of Atos Group is to help design the future of the information space. Its expertise and services support the development of knowledge, education and research in a multicultural approach and contribute to the development of scientific and technological excellence. Across the world, the Group enables its customers and employees, and members of societies at large to live, work and develop sustainably, in a safe and secure information space.

Apps AI Architect 539988

Location: North America (Remote)

Role Summary

The Apps AI Architect will play a pivotal role in transforming how we design, build, and manage enterprise applications in the GenAI era. This role blends deep application architecture expertise - spanning UI/UX, front-end, back-end, integration, data, and cloud - with hands-on AI engineering skills to infuse Artificial Intelligence (including Generative and Agentic AI) across the full application lifecycle - from design and development to modernization and ongoing operations. The Architect will drive innovation, develop reusable AI patterns, and deliver proof-of-value (PoV) initiatives that convert emerging technology possibilities into tangible business impact.

Key Responsibilities

  • Architect AI-Native Applications: Design and implement architectures that integrate AI models (LLMs, predictive, and agentic systems) into application workflows to enable reasoning, automation, and contextual decision-making.
  • End-to-End Application Design: Lead the design of UI/UX flows, user-facing AI interactions, conversational interfaces, and AI-augmented user journeys across web and mobile applications.
  • Drive Modernization Through AI: Reimagine legacy and digital applications by embedding AI capabilities that enable modernization, optimization, and transformation across app portfolios. Design modernization frameworks leveraging AI for architecture discovery, business-rules extraction, and application rationalization. Embed intelligence in re-platformed or refactored applications to create truly AI-native modernization.
  • Legacy-to-Modern Mapping: Architect solutions that transform legacy applications into modern Java, .NET, microservices, or cloud-native platforms while preserving core business rules and logic.
  • Infuse AI Across Dev & Ops: Partner with delivery and support teams to embed AI in software engineering, testing, incident management, and observability - driving efficiency, resilience, and proactive operations.
  • Tooling & Frameworks: Evaluate, integrate, and optimize AI-assisted tools (e.g., code translators, test generators, documentation bots) within modernization pipelines to accelerate delivery.
  • Integration & Ecosystem: Define strategies to integrate modernized applications into enterprise ecosystems, including APIs, event-driven architectures, and cloud environments.
  • Lead Proofs of Value (PoVs): Design and execute AI-centric PoVs to validate new technologies, tools, and architectures for clients.
  • Collaborate & Evangelize: Partner with pre-sales, delivery, and client stakeholders to identify AI opportunities, shape proposals, and articulate the business value of AI-native transformation.
  • Develop Reusable Assets: Create frameworks, accelerators, and reference architectures to scale adoption of GenAI and LLM-enabled solutions across multiple accounts.

Required Skills & Experience

  • 10-15 years of experience in Application Architecture, Engineering, or Digital Transformation, with at least 2-3 years in AI/ML or GenAI implementation.
  • Strong experience with Azure OpenAI, OpenAI APIs, Vertex AI, AWS Bedrock, LangChain, LlamaIndex, or similar LLM platforms.
  • Deep understanding of modern UI/UX architecture, responsive front-end design, and frameworks such as React, Angular, Vue, or equivalent.
  • Proficiency in Python, Node.js, or Java, with exposure to LLM integration, prompt engineering, and API orchestration.
  • Experience with leading AI-assisted productivity tools such as Claude, Gemini Code Assist, and GitHub Copilot.
  • Familiarity with observability and AIOps platforms including DataDog, Dynatrace, Moogsoft, Splunk AIOps, and ServiceNow AIOps.
  • Hands-on exposure to LLM-based ITSM agents and RAG (Retrieval-Augmented Generation) frameworks.
  • Experience with MLOps/GenAIOps for continuous model improvement within modernization initiatives.
  • Strong background in application modernization (re-platforming, containerization, microservices, and cloud-native design).
  • Solid understanding of legacy technologies such as Mainframe, Java, and .NET.
  • Knowledge of PromptOps, model observability, AI lifecycle management, and related operational frameworks.
  • Excellent communication, stakeholder management, and customer-facing engagement skills.

Preferred Qualifications

  • Certifications in AI Engineering (Azure, AWS, or Google) or equivalent credentials.
  • Prior experience working in Application Services, AMS, or ADM environments.
  • Exposure to agentic workflows, AI observability, or RAG (retrieval-augmented generation) frameworks.
  • The role requires active engagement across the full lifecycle - from pre-sales solution shaping through design, development, implementation, and ongoing evolution of AI-native applications.
  • Given the evolving nature of AI-native architectures, we welcome candidates who may not meet every requirement but demonstrate strong foundational skills and the ability to grow into the role.

Why This Role Matters

This role is central to our AI-Native Application Services transformation. The Apps AI Architect will directly shape how enterprise applications evolve - blending the power of AI, data, and cloud to create intelligent, adaptive, and self-improving systems that redefine how our clients build, run, and scale their businesses.

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