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Entry Level Llm Engineer Jobs in Seattle, WA (NOW HIRING)

Entry Level Llm Engineer information

See Seattle, WA salary details

$46.1K

$98.3K

$162.2K

How much do entry level llm engineer jobs pay per year?

As of Aug 16, 2026, the average yearly pay for entry level llm engineer in Seattle, WA is $98,304.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,000.00 and $117,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an entry level LLM engineer, and why are they important?

To thrive as an Entry Level LLM Engineer, you need a solid background in computer science, programming (especially Python), and basic machine learning concepts, often supported by a relevant degree. Familiarity with machine learning frameworks (like TensorFlow or PyTorch), experience with LLM APIs (such as OpenAI or Hugging Face), and understanding version control systems (like Git) are typically expected. Strong problem-solving skills, attention to detail, and effective communication help you collaborate and adapt in dynamic teams. These competencies are crucial for building, fine-tuning, and deploying large language models that meet project goals and industry standards.

What is an entry level LLM engineer?

An Entry Level LLM (Large Language Model) Engineer is a professional who works on developing, fine-tuning, and deploying AI models that process and generate human language, such as GPT or similar neural network-based systems. They typically work with machine learning frameworks, data preprocessing, and model evaluation under the guidance of more experienced engineers. Entry level LLM Engineers are often responsible for implementing basic model architectures, running experiments, and analyzing model performance. They usually have a background in computer science, machine learning, or related fields, and are familiar with programming languages like Python.

What are some common challenges faced by entry level LLM engineers when working on real-world language model applications?

Entry Level LLM Engineers often encounter challenges such as adapting large language models to specific business requirements, managing computational resources efficiently, and debugging complex model outputs. Collaborating with data scientists and software engineers is key, as projects typically require integrating models into broader systems. Additionally, staying updated with rapid advancements in the field and learning to work with large datasets are ongoing aspects of the role. Supportive team structures and mentorship can help new engineers overcome these hurdles and accelerate their growth.

What are the most commonly searched types of Llm Engineer jobs in Seattle, WA?

The most popular types of Llm Engineer jobs in Seattle, WA are:

Infographic showing various Entry Level Llm Engineer job openings in Seattle, WA as of August 2026, with employment types broken down into 90% Full Time, 4% Part Time, and 6% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution, with an average salary of $98,304 per year, or $47.3 per hour.

Junior Software Engineer, AI-Native (SEATTLE ONLY)

Pipe17

Seattle, WA

Full-time

Posted 23 days ago


Job description

Junior Software Engineer, AI-Native (SEATTLE ONLY)

On-site, Seattle

We are not sponsoring any work authorizations at this time.

About Pipe17

Pipe17 is building the AI operating system for commerce. Our platform connects brands, retailers, marketplaces, warehouses, ERPs, and shipping providers to automate order operations at scale, processing millions of commerce events a day so customers eliminate manual work, cut complexity, and move faster. We build software that doesn't just help people do the work, it does the work.

The Role

We're hiring an AI-native Junior Software Engineer to build software with AI across two fronts: internal tools that make our team faster, and customer-facing product. This is not a pure internal-automation role. You'll automate the messy work that slows engineering and the business down, and you'll also ship product features and agents that customers use. We want the balance of both.

You already build with AI. You reach for coding agents and LLMs the way other engineers reach for a framework, and you have a track record of shipping real things with them, not just experimenting. AI does the heavy lifting on the platform layer; your job is to point it at the right problems and ship.

Interview note: part of the process is a live working session. You'll screen share and build with the AI tool of your choice, then we'll program together. We can provide an Anthropic API key for the interview (Claude Code, Cursor, or others) if you'd rather not use your own.

What You'll Do

  • Build software with AI across two fronts: internal tools that make the team faster, and customer-facing product features and agents.
  • Design, build, and maintain automations, lightweight APIs, CLI tools, and web utilities in JavaScript / TypeScript.
  • Build and integrate agents and AI-powered features into real workflows and the product, using Claude, Claude Code, and other LLM APIs.
  • Implement and manage MCP / API integrations between internal systems and external services (GitHub, Jira, HubSpot, NetSuite, or internal APIs).
  • Partner with product and platform engineering to turn messy problems into shipped software.
  • Troubleshoot integration and system issues across environments; write clear docs and onboard teammates to what you build.
  • Take part in design reviews, stand-ups, and sprint planning; contribute to testing for tools, APIs, and product.

What You'll Learn

Hands-on experience with:

  • Node.js / TypeScript for automation, APIs, product features, and developer tooling
  • REST / GraphQL APIs for integration and data sync
  • Building with AI: Claude, Claude Code, Codex and other LLM-based systems and agents
  • Infrastructure scripting and configuration (AWS, Terraform, Docker)
  • Authentication and authorization flows (OAuth2, API keys, JWT)
  • CI/CD automation (GitHub Actions or similar)
  • Cloud deployments (AWS Lambda, ECS, or similar containerized services)
  • Observability and monitoring (CloudWatch, Datadog, Grafana)
  • Secure, SOC 2-aligned development practices

What We're Looking For

Required

  • 1-2 years out of college in software engineering, with a strong CS background.
  • A demonstrated track record of building software with AI: agents, tools, or product you've actually shipped, not just tried.
  • Think deeply about customer challenges and problems
  • Fluency in JavaScript / TypeScript.
  • Experience building tools or automations and integrating APIs (REST, GraphQL, or webhooks).
  • Daily fluency with AI developer tools (Claude Code, Cursor, GitHub Copilot, or similar).
  • Familiarity with Git, CI/CD, and a cloud platform (AWS or similar).
  • Strong problem-solving, communication, and ownership. You ask why, challenge assumptions, and love to automate messy problems.

Nice-to-Have

  • SQL / NoSQL databases
  • Containerization (Docker) or serverless platforms
  • Python or Bash scripting
  • Interest in e-commerce or logistics tech

Why It Matters

Pipe17 powers the flow of orders and shipments for some of the fastest-growing brands in e-commerce. You'll build the tools that make our engineers faster and the product features customers feel, and you'll see how AI-assisted development scales in a real production SaaS environment.

What We Offer

  • Competitive entry-level salary and benefits
  • Mentorship from senior engineers and architects on an AI-native team
  • Real production ownership, with work that ships weekly
  • A clear path to mid-level roles in software, AI + integrations, or platform engineering

How We Work

We value clarity, curiosity, and ownership. You'll join a small, high-agency team where your work ships weekly and lands in both our internal systems and the product our customers use. We build with AI first, and we expect you to do the same.

Pipe17 is an equal opportunity employer. We celebrate diversity and are committed to an inclusive environment for all employees.