1

Ai Coding Jobs in Redmond, WA (NOW HIRING)

AI Engineer Intern

Bellevue, WA · On-site

$82.66 - $165.31/hr

Proficient with AI coding tools and prompt engineering--you've built with these, not just experimented * Prior professional experience not required if portfolio demonstrates real AI engineering ...

New

Senior Front-end Engineer, AI

Seattle, WA · On-site

$139K - $191K/yr

Write beautiful, self-documenting code that others can easily read and adapt * Write and review ... Is embracing the future of software engineering, employing AI coding tools to amplify your ...

You will use modern AI coding assistants day-to-day to design and implement solutions, and you're expected to be fluent extending that toolset - building custom plugins/skills, redesigning data ...

Agentic AI Engineer

Seattle, WA · On-site +1

$145K/yr

Agentic AI Engineer Envorso Sports Seattle, WA (Hybrid) or Remote, US Full-time -8d55-4962-b372 ... coding agents can touch, PR-review agents that check against the spec, and automated checks that ...

New

Technical Product Manager, AI

Bellevue, WA · On-site

$188K - $217K/yr

Build working prototypes yourself using AI coding agents and modern tooling (Claude Code, Cursor, LLM APIs) to validate feasibility and de-risk designs before committing engineering resources.

Showing results 21-40

Ai Coding information

See Redmond, WA salary details

$15

$36

$61

How much do ai coding jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for ai coding in Redmond, WA is $36.98, according to ZipRecruiter salary data. Most workers in this role earn between $27.98 and $44.71 per hour, depending on experience, location, and employer.

What is an AI coding?

An AI Coding job involves developing, training, and optimizing artificial intelligence models and algorithms. Professionals in this role typically work with machine learning, deep learning, and data processing to create AI-driven applications. They use programming languages like Python and frameworks such as TensorFlow or PyTorch to build intelligent systems. AI coders may also fine-tune models, improve efficiency, and deploy AI solutions for various industries.

What does an AI coder do?

Professionals in AI Coding typically spend their days designing, writing, and debugging code for machine learning models or AI-driven applications. They often collaborate with data scientists, product managers, and engineers to define project requirements, process data, and integrate AI solutions into existing systems. Regular tasks may include training and testing models, improving algorithm performance, and documenting code or processes. You’ll also likely participate in team meetings and code reviews to ensure alignment and maintain high-quality standards. This dynamic environment provides continuous opportunities to learn and innovate within the field of artificial intelligence.

What skills and qualifications are needed for AI coding?

To thrive in an AI Coding role, a strong background in computer science, programming languages (such as Python or Java), and machine learning fundamentals is essential. Familiarity with AI frameworks (like TensorFlow, PyTorch), cloud platforms, and relevant certifications (such as TensorFlow Developer Certificate) is highly valuable. Strong analytical thinking, creativity, and effective teamwork are important soft skills for excelling in this position. These skills ensure you can develop robust AI solutions, adapt to evolving technologies, and collaborate effectively with cross-functional teams.

How do I become an AI coder?

To become an AI coder, you should develop strong programming skills in languages like Python, learn machine learning frameworks such as TensorFlow or PyTorch, and gain knowledge of algorithms and data structures. Pursuing relevant education, such as a degree in computer science or related fields, and working on AI projects or internships can also help build practical experience.

What are popular job titles related to Ai Coding jobs in Redmond, WA?

For Ai Coding jobs in Redmond, WA, the most frequently searched job titles are:

What job categories do people searching Ai Coding jobs in Redmond, WA look for?

The top searched job categories for Ai Coding jobs in Redmond, WA are:

What cities near Redmond, WA are hiring for Ai Coding jobs?

Cities near Redmond, WA with the most Ai Coding job openings:

Infographic showing various Ai Coding job openings in Redmond, WA as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 69% Physical, 4% Hybrid, and 27% Remote job distribution, with an average salary of $76,922 per year, or $37 per hour.

Principal DevOps Engineer (AI Enablement) (Bellevue)

Guidacent, Inc.

Bellevue, WA • On-site

$59.25 - $81/hr

Full-time

Re-posted 7 days ago


Job description

Guidacent is seeking a Principal DevOps Engineer experienced in AI daily use to improve individual and team work efforts. This is a senior individual-contributor role with significant influence: the right candidate will architect the delivery platform and developer experience (DevEx), define standards and reusable “paved roads,” make cross-team technical decisions, and mentor other engineers. We are looking for a strong DevOps practitioner first — someone deep in CI/CD, infrastructure-as-code, cloud, containers, and observability — who has folded AI tooling such as Claude or Cursor into their daily workflow and used it to make engineering standards and practices measurably better. Just as important, the right candidate knows how to be a careful, cost-aware user of these tools: getting real leverage from AI without token overuse. The role extends proven DevOps practice with AIOps and AI-assisted automation, and treats DevEx as a long‑term, principal‑owned concern. Formal people or team management is a welcome plus but not a requirement, but preference is for a hands‑on principal-level IC and player‑coach who wants to lead a team. Candidates MUST be located in the Greater Seattle area and be willing to work onsite.

Key Responsibilities
  • Technical direction & architecture: Own the architecture for CI/CD, infrastructure, and the AI delivery platform; set the technical strategy and reference architectures that other teams build on.
  • Developer experience (DevEx): Own developer experience as a long‑term, principal-level charter — continuously improve how engineers build, test, and ship, and treat DevEx as a product with its own metrics and roadmap.
  • Standards & paved roads: Define and champion reusable templates, golden paths, and engineering standards that make delivery fast, safe, and self‑service — using AI tooling to raise the bar on those standards, not just to move faster.
  • AI in the daily workflow: Set the example and the patterns for using AI coding tools (e.g., Claude, Cursor) day to day, and turn that hands‑on use into improved practices, reviews, and automation across the team — with disciplined, cost‑aware token usage rather than wasteful consumption.
  • CI/CD delivery: Lead the design of continuous integration and deployment pipelines with automated testing, validation, and rollback.
  • Infrastructure as code: Establish IaC and GitOps practices (Terraform or equivalent) across one or more major clouds.
  • Scaling AI tooling & AIOps: Drive org-wide adoption of AI‑assisted review, test generation, and AIOps‑driven incident detection and remediation, and quantify their impact on quality, velocity, and reliability.
  • Observability & AIOps: Define observability strategy — telemetry, logging, automated anomaly detection, and alerting — and apply AIOps techniques to set SLOs that reduce mean‑time‑to‑resolution.
  • DevSecOps & responsible AI use: Embed security scanning, secrets management, and sensible guardrails for how AI tooling is used (e.g., data handling, access, and review practices) across the delivery lifecycle.
  • Reliability & cost: Set reliability practices (SLOs, DORA metrics) and optimize infrastructure and tooling cost — including efficient, token‑aware use of AI tools.
  • Mentorship & influence: Mentor and uplevel engineers, lead technical reviews, and influence the broader engineering roadmap and ways of working.
Required Qualifications
  • MUST be located in the Greater Seattle area and be willing to work onsite.
  • 8+ years in DevOps, platform engineering, or site reliability engineering, including a track record of senior technical ownership.
  • Demonstrated experience architecting and setting direction for CI/CD and infrastructure platforms used across multiple teams.
  • Strong CI/CD experience (e.g., GitHub Actions, GitLab CI, Jenkins, or Azure DevOps).
  • Deep proficiency with infrastructure-as-code (Terraform, Pulumi, or CloudFormation) and at least one major cloud (AWS, Azure, or GCP).
  • Hands‑on containerization and orchestration with Docker and Kubernetes, including production‑scale operations.
  • Strong scripting and automation skills in Python, Bash, or Go.
  • Experience defining observability and monitoring strategy (e.g., Prometheus, Grafana, Datadog, ELK).
  • Regular, hands‑on use of AI to make DevOps work more efficient — automating tasks, generating and reviewing code, troubleshooting, and improving tooling.
  • Daily, hands‑on use of AI coding tools (e.g., Claude, Cursor, or equivalent) as a core part of how they work — with a cost‑conscious, token‑aware approach rather than wasteful consumption.
  • A demonstrated track record of using AI to make engineering standards and practices measurably better (e.g., better reviews, tests, automation, or paved‑road tooling), not just to ship faster.
  • Some level of AIOps experience — using AI‑driven techniques for monitoring, anomaly detection, alerting, or automated remediation.
  • Genuine interest in and ownership instinct for developer experience (DevEx) as a long‑term concern.
  • Proven ability to mentor engineers, lead technical decisions, and influence across teams.
Preferred Qualifications
  • People or team management experience — leading, growing, or formally managing a DevOps / platform / DevEx team. A strong plus for candidates on a player‑coach or principal‑with‑reports path, but not required.
  • Experience standing up or owning a platform or developer‑experience function from the ground up.
  • Experience evaluating, rolling out, and measuring AI developer tools (e.g., Claude, Cursor, Copilot) across a team or organization.
  • Familiarity with AIOps platforms and automated remediation.
  • Cost / FinOps discipline for cloud and AI tooling — monitoring and optimizing spend, including token usage.
  • Awareness of responsible / secure AI‑use practices and relevant data‑handling requirements.
  • Relevant certifications (CKA/CKAD, cloud architect or DevOps engineer, Terraform Associate).
  • Exposure to enterprise ITSM/ITOM platforms (e.g., ServiceNow) and large‑scale program environments.
#J-18808-Ljbffr