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Remote Python Llm Jobs in Remote, OR (NOW HIRING)

Atos

Apps AI Solution Architect AMS

OR · Remote

$59 - $77.75/hr

North America (Remote) Role Summary The Apps AI Architect will play a pivotal role in transforming ... Proficiency in Python, Node.js, or Java, with exposure to LLM integration, prompt engineering, and ...

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Remote Python Llm information

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$58

$86

How much do remote python llm jobs pay per hour?

As of Jul 10, 2026, the average hourly pay for remote python llm in Remote, OR is $58.56, according to ZipRecruiter salary data. Most workers in this role earn between $48.27 and $66.54 per hour, depending on experience, location, and employer.

What remote jobs can you get with Python?

Remote Python jobs include roles such as software developer, data analyst, machine learning engineer, and automation engineer. These positions often require proficiency in Python programming, familiarity with frameworks like Django or Flask, and experience with cloud platforms or version control tools. Many of these jobs offer flexible schedules and can be performed from any location with internet access.

Will AI replace Python devs?

Remote Python developers are unlikely to be fully replaced by AI, as their role involves complex problem-solving, coding, and adapting to new requirements that AI tools currently cannot fully replicate. AI can assist by automating repetitive tasks and improving productivity, but human oversight and expertise remain essential for software development. Staying updated with new tools and skills can help Python developers remain valuable in an evolving tech environment.

What is a Remote Python LLM job?

A Remote Python LLM job typically involves working with large language models (LLMs) like GPT or similar AI technologies using the Python programming language, while operating remotely. Professionals in this role develop, fine-tune, and deploy machine learning models, especially those focused on natural language processing (NLP) tasks. Responsibilities may include building Python applications that integrate with LLMs, data preprocessing, and collaborating with teams across different locations. The remote aspect allows for flexible work arrangements and access to global opportunities.

What are some common collaboration methods used by Remote Python LLM engineers when working with cross-functional teams?

Remote Python LLM engineers frequently collaborate with data scientists, product managers, and other developers through virtual meetings, code reviews, and shared documentation platforms. Tools like Slack, GitHub, and Jira are often used to ensure smooth communication and project tracking, despite working across different time zones. Regular stand-ups and sprint planning sessions help align objectives and keep everyone updated on progress. Proactive communication and clear documentation are key to overcoming the challenges of remote, distributed teamwork in this role.

Is Python used in LLM?

Yes, Python is widely used in developing large language models (LLMs) and is a key skill for remote Python LLM roles. It provides extensive libraries and frameworks such as TensorFlow and PyTorch that facilitate model training, fine-tuning, and deployment.

What are the key skills and qualifications needed to thrive as a Remote Python LLM Engineer, and why are they important?

To thrive as a Remote Python LLM Engineer, you need strong proficiency in Python programming, experience with large language models (LLMs), and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), cloud platforms, and version control systems like Git is typically required. Excellent problem-solving abilities, self-motivation, and effective communication are crucial soft skills for remote collaboration and troubleshooting. These skills ensure you can develop, deploy, and maintain advanced language models efficiently while working independently in distributed teams.

Which LLM is good for Python coding?

For a Remote Python Llm role, models like OpenAI's GPT-4 and GPT-3.4 are widely used for Python coding due to their strong language understanding and code generation capabilities. Additionally, open-source models such as Meta's Llama 2 and EleutherAI's GPT-NeoX can be fine-tuned for specific coding tasks, making them suitable options for development environments requiring customization. Proficiency in integrating these models with APIs and understanding their limitations is essential for effective Python coding assistance.
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Remote Python Llm jobs near you

Apps AI Solution Architect AMS

Atos

OR • Remote

$59 - $77.75/hr

Other

Re-posted 17 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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