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Genai Developer Jobs in Remote, OR (NOW HIRING)

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 ...

Head of AI

OR · Remote

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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... traces across developer machines, scrubs sensitive content centrally in Azure, and serves a ... LLM-agent or GenAI observability exposure * Cross-cloud identity federation (AAD ⇄ GCP IAM) Perks ...

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Genai Developer information

See Remote, OR salary details

$17

$52

$81

How much do genai developer jobs pay per hour?

As of Sep 6, 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 is a GenAI developer?

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 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 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 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.

How to become a GenAI developer?

To become a GenAI developer, you should gain expertise in machine learning, deep learning, and natural language processing, with a focus on generative models like GPT. Proficiency in programming languages such as Python, experience with frameworks like TensorFlow or PyTorch, and understanding of large language models are essential. Building a portfolio of projects and staying updated with AI research can also enhance your qualifications.

Is a Genai Developer a promising career?

A Genai Developer is a growing role focused on developing and implementing generative AI models, which are increasingly used across industries. The field requires skills in machine learning, programming, and AI frameworks, and offers strong job growth prospects due to expanding AI adoption. Continuous learning and staying updated with new tools are important for success in this career.
Infographic showing various Genai Developer job openings in Remote, OR as of August 2026, with employment types broken down into 80% Full Time, 4% Part Time, and 16% Contract. Highlights an 75% Physical, 5% Hybrid, and 20% Remote job distribution, with an average salary of $109,796 per year, or $52.8 per hour.

Head of AI

Atos

OR • On-site, Remote

Full-time

Re-posted 29 days ago


Key responsibilities

  • Define and execute the North America AI practice strategy and capability roadmap.

  • Support the development of packaged offerings, industry-specific solutions, and represent the company externally through thought leadership activities.

  • Own pipeline and bookings targets, ensure high-quality delivery, and build and scale the AI team.


Job description

About Atos Group
Atos Group is a global leader in digital transformation with c. 67,000 employees and annual revenue of c. €10 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.
Position : Head of Artificial Intelligence
Role Summary
The Head of Artificial Intelligence Practice (North America) leads strategy, growth, delivery excellence, and talent for the AI portfolio across U.S. and Canada. This executive role owns practice P&L, builds scalable offerings (GenAI, ML, data science, AI platforms, MLOps), and partners with sales and delivery leaders to expand revenue and customer impact across industries.
Reporting and Scope
  • Reports to: Head of Data & AI - North America
  • Direct reports: AI practice leadership team (solution leads, delivery leaders, architects), plus dotted-line matrix teams
  • Geography: United States and Canada (remote/hybrid depending on location)
  • Travel: Up to 25-40% (client sites, executive briefings, industry events)

Key Responsibilities
• Practice strategy and roadmap
    • Define the North America AI practice strategy aligned to corporate goals and market demand.
    • 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 prioritize investments for impact and scale.
    • Lead the delivery team for AI across NA including building and managing talent and ensuring ulitization targets for the team

• Portfolio, offerings, and thought leadership
    • Support Head of Advisory and Global Teams with packaged offerings and accelerators (POCs-to-production playbooks, reference architectures, reusable components).
    • Work with Head of Innovation industry-specific solutions (e.g., banking, retail, healthcare, telecom, public sector) with measurable outcomes.
    • Represent the company externally through speaking, publishing, analyst briefings, and customer success stories.

• Go-to-market and revenue growth
    • Own pipeline and bookings targets for AI services in North America; partner with sales, alliances, and marketing.
    • Help Represent the solutioning for strategic pursuits, including executive-level proposal narratives, value cases, and pricing models.
    • Help support the partner ecosystem with hyperscalers and AI platform vendors; drive co-sell motions where applicable.

• Delivery excellence and customer outcomes
    • Ensure high-quality delivery across AI engagements, with strong governance, risk management, and stakeholder communication.
    • Standardize delivery methodology for AI programs (discovery, prototyping, productionization, monitoring, continuous improvement).
    • Drive customer adoption, measurable business value, and referenceability through disciplined success management.

• Talent, org design, and culture
    • Build and scale a high-performing AI team: hiring plans, skills frameworks, career paths, and mentorship.
    • Upskill broader delivery teams through training programs, communities of practice, and internal enablement.
    • Foster a culture of engineering rigor, responsible AI, collaboration, and continuous learning.

• Governance, security, and responsible AI
    • Establish responsible AI standards (privacy, security, bias mitigation, explainability, model risk management).
    • Partner with security, legal, and compliance teams to ensure AI solutions meet client and regulatory requirements.
    • Define and monitor AI practice quality standards, including data governance, model lifecycle controls, and audits.

• Financial management and operations
    • Help support the Head of Data and AI P&L: revenue, gross margin, utilization, bench, subcontractor mix, and investment planning.
    • Set operating rhythm: QBRs, forecast accuracy, capacity planning, and delivery health dashboards.
    • Optimize delivery model (onshore/nearshore/offshore) to meet client needs and margin targets.

Required Qualifications
  • 15+ years of experience in technology consulting, product engineering, or enterprise technology leadership, with 8+ years in AI/ML/GenAI leadership.
  • Proven track record building and scaling an AI practice or portfolio with P&L responsibility and measurable revenue growth.
  • Strong understanding of modern AI stack: GenAI (LLMs), Agentic AI, ML, data engineering, AI platforms, MLOps/LLMOps, and cloud services (AWS/Azure/GCP).
  • Demonstrated experience delivering AI solutions end-to-end: discovery to production, monitoring, and continuous improvement.
  • Executive presence with ability to influence EVP-level stakeholders and lead complex deal pursuits.
  • Experience leading multi-disciplinary teams (AI Architects, AI Engineers, data scientists, ML engineers, architects, product managers, delivery leaders).
  • Knowledge of responsible AI, security, and privacy requirements for enterprise AI implementations.

Preferred Qualifications
  • Experience in IT services/consulting organizations operating with global delivery models (onshore/nearshore/offshore).
  • Domain expertise in one or more regulated industries (financial services, healthcare, telecom, government).
  • Partnership experience with hyperscalers and AI platform vendors; co-sell and alliance management success.
  • Hands-on experience with AI solution architecture, including retrieval-augmented generation (RAG), vector databases, and agentic workflows.
  • Advanced degree in Computer Science, Engineering, Data Science, or related field; MBA a plus.

Core Competencies
  • Strategic leadership and business building
  • Consultative selling and executive stakeholder management
  • AI engineering rigor and delivery governance
  • Productization mindset (offerings, accelerators, repeatability)
  • Talent development and organizational design
  • Cross-functional collaboration in matrix environments
  • Strong communication: narrative building, proposals, and presentations

Tools and Technologies (Representative)
  • Cloud: AWS, Microsoft Azure, Google Cloud Platform
  • AI/ML: Agentic AI, Python, PyTorch/TensorFlow, scikit-learn, MLflow (or equivalent), feature stores
  • GenAI: LLM APIs and platforms, prompt engineering, RAG patterns, evaluation frameworks, guardrails
  • Data: SQL, modern data warehouses/lakehouse platforms, streaming where needed
  • MLOps/LLMOps: CI/CD for models, monitoring/observability, model registry, governance tooling

Work Environment
  • Remote or hybrid within North America; may require proximity to major client hubs.
  • Travel expectation up to 25-40% based on client needs and business development cycles.
  • This role may require occasional work outside standard business hours to support executive meetings across time zones.

Equal Opportunity
The organization is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Here at Atos, diversity and inclusion are embedded in our DNA. Read more about our commitment to a fair work environment for all.
Atos is a recognized leader in its industry across Environment, Social and Governance (ESG) criteria. Find out more on our CSR commitment.
Choose your future. Choose Atos.