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Genai Jobs in Remote, OR (NOW HIRING)

Atos

Head of AI

OR · On-site +1

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 ...

Atos

Head of AI

OR · On-site +1

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 ...

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Genai information

Is generative AI a good career?

Generative AI is a growing field with increasing demand for professionals skilled in machine learning, deep learning, and natural language processing. Careers in this area often require knowledge of programming languages like Python and familiarity with AI frameworks such as TensorFlow or PyTorch. The field offers opportunities in research, development, and deployment across various industries, making it a promising career choice for those with technical expertise.

Which 3 jobs will survive AI?

GenAI professionals, healthcare workers, and skilled tradespeople are likely to continue thriving as AI automates routine tasks but requires human oversight, empathy, and specialized skills. These roles involve complex decision-making, emotional intelligence, or physical craftsmanship that AI cannot easily replicate. Continuous learning and certification in relevant tools or techniques can enhance job security in these fields.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior machine learning engineer, AI research director, or executive roles, which offer compensation in that range including salary, bonuses, and stock options. These roles often require advanced skills in AI, deep learning, data science, and experience with tools like TensorFlow or PyTorch, along with a strong educational background and industry experience.

What are GenAI jobs?

GenAI jobs involve developing, training, and deploying generative artificial intelligence models that create content such as text, images, or audio. These roles typically require skills in machine learning, deep learning frameworks, and programming languages like Python, often within tech or research environments. Professionals in this field work on improving AI capabilities and ensuring ethical use of generative models.

What are the typical day-to-day responsibilities of a GenAI Specialist?

As a GenAI Specialist, your typical day may involve designing, developing, and optimizing generative AI models for various applications, such as natural language processing or image synthesis. You'll often collaborate closely with data scientists, software engineers, and product teams to align AI solutions with business needs. Tasks may include data preprocessing, model evaluation, fine-tuning algorithms, and addressing ethical or bias considerations in AI outputs. You may also participate in research initiatives, documentation, and client presentations, offering a dynamic and intellectually stimulating work environment.

What is a GenAI job?

A GenAI (Generative AI) job involves working with artificial intelligence models that generate text, images, code, or other content. Roles in this field can include AI research, machine learning engineering, prompt engineering, or AI ethics. Professionals in GenAI work with large language models (LLMs) and deep learning frameworks to refine AI-generated outputs and integrate them into applications. These jobs are found in industries like tech, marketing, healthcare, and finance, where AI-powered automation and content generation are valuable.

What are the key skills and qualifications needed to thrive in the Genai position, and why are they important?

To excel as a GenAI (Generative AI Specialist), you need a strong background in computer science, machine learning, and artificial intelligence, typically with a relevant degree and experience in training large language models. Familiarity with tools and frameworks such as Python, TensorFlow, PyTorch, and cloud platforms is highly valued, along with certifications like AWS Certified Machine Learning or Google Professional Data Engineer. Strong analytical thinking, creativity, and collaborative communication are standout soft skills in this field. These competencies ensure effective model development, seamless teamwork, and the ability to deliver innovative AI solutions in business contexts.

What job categories do people searching Genai jobs in Remote, OR look for? The top searched job categories for Genai jobs in Remote, OR are:
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Infographic showing various Genai job openings in Remote, OR as of July 2026, with employment types broken down into 93% Full Time, 3% Part Time, and 4% Contract. Highlights an 77% Physical, 5% Hybrid, and 18% Remote job distribution.

Head of AI

Atos

OR • On-site, Remote

Full-time

Posted 18 days ago

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.

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