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Ai Agent Engineer Jobs in Portland, OR (NOW HIRING)

AI Engineer

Portland, OR · On-site

$50K - $112K/yr

... agent workflows using frameworks such as LangGraph to automate multi-step reasoning, integrate tools and APIs, and deliver scalable, context-aware solutions - Applying generative AI techniques ...

Software Engineer

Beaverton, OR · On-site

$85 - $105/hr

Install TAL for a 24/7 AI agent that keeps finding roles personalised for you.Apply nowInstall ... Master's degree in CS, Engineering, CIS, or Mathematics* 1 year of experience in the job offered or ...

Sr. AI Software Engineer - Agent Harness

Hillsboro, OR · On-site

$133K - $175K/yr

This is core product engineering on an agent framework comparable to well know AI models, but built to run hybrid (local + cloud) and with efficiency. What you'll do: * Design and build the agent ...

Designing and delivering embedded artificial intelligence (AI) agent capabilities within Oracle ... Bachelor's degree or higher in computer science, information technology, software engineering ...

Familiarity with M365 Copilot features or similar AI bot/agent development tools (e.g. Azure AI services, cognitive services). * Programming Skills: Proficiency in at least one programming or ...

Familiarity with M365 Copilot features or similar AI bot/agent development tools (e.g. Azure AI services, cognitive services). Programming Skills: Proficiency in at least one programming or scripting ...

AI Engineer, Sr

Newberg, OR · On-site

$109K - $150K/yr

AI Engineer, Sr At A-dec, we do more than create the highest quality products and services for the ... Design and orchestrate multi agent AI systems, including LLM based agents, agent routing and ...

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Ai Agent Engineer information

See Portland, OR salary details

$27

$56

$81

How much do ai agent engineer jobs pay per hour?

As of Sep 4, 2026, the average hourly pay for ai agent engineer in Portland, OR is $56.88, according to ZipRecruiter salary data. Most workers in this role earn between $45.87 and $66.01 per hour, depending on experience, location, and employer.

What is an AI Agent engineer?

An AI Agent Engineer designs, develops, and optimizes autonomous AI agents that can perceive, reason, and act within digital or real-world environments. They work with machine learning, reinforcement learning, and natural language processing to build intelligent systems that interact dynamically with users and other agents. These engineers often integrate AI models with APIs, databases, and software applications to create functional and scalable AI-driven solutions. Their role bridges software engineering and artificial intelligence, ensuring agents operate efficiently and adaptively in various use cases.

What are the key skills and qualifications needed to thrive as an AI Agent engineer?

To excel as an AI Agent Engineer, you need a robust background in computer science, machine learning, and software engineering, often supported by a degree in a STEM field. Familiarity with programming languages like Python, relevant AI frameworks (such as TensorFlow or PyTorch), and experience with cloud platforms are typically expected, along with certifications in AI or data science being advantageous. Strong problem-solving abilities, effective communication, and teamwork skills are essential soft skills for collaborating on complex AI projects. These competencies ensure you can design, implement, and refine intelligent agents that meet real-world challenges and deliver business value.

What are some typical challenges faced by AI Agent engineers in their day-to-day work?

AI Agent Engineers often encounter challenges such as optimizing agent performance for real-time environments, integrating new algorithms without disrupting existing systems, and ensuring their models can handle diverse and dynamic real-world data. Troubleshooting unexpected behaviors or edge cases and keeping up with rapidly evolving research in artificial intelligence can also be demanding. Working closely with product managers, data scientists, and software developers helps address these challenges, making collaboration and adaptability key components of daily tasks. Overcoming these issues offers valuable learning opportunities and contributes to the growth of robust, innovative AI solutions.

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Cities near Portland, OR with the most Ai Agent Engineer job openings:

Infographic showing various Ai Agent Engineer job openings in Portland, OR as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 70% Physical, 4% Hybrid, and 26% Remote job distribution, with an average salary of $118,104 per year, or $56.8 per hour.

AI Agent Trajectory Annotator and Reviewer

Bespoke Labs

Portland, OR • On-site

$20 - $30/hr

Full-time

Posted 3 days ago

New


Job description

Type: Contract, hourly

Location: Remote

Hours: 20–30 per week

Pay: $20–30/hour, based on experience and language coverage

Start: Immediate

ABOUT THE ROLE

We evaluate how well advanced AI coding agents solve real engineering problems. An agent is given a real open source codebase inside a container and a hard task, then works on its own for 80 to 250 steps. A trajectory is the full record of that run — every command, result, and decision.

You will do two jobs, and you should expect either on any given day.

•Annotate — Read a trajectory nobody has looked at yet and judge it step by step.

• Review — Take an existing annotation, written by our AI tooling or another person, and confirm, correct, or reject it.

TASKS YOU'LL SEE

• Feature build — Add a working feature to a live library without breaking anything that already worked.

• Rebuild — Work out what a compiled tool does by running it, then rebuild it to match its output, exit codes, and file effects.

• Bug hunt — Find and fix twenty undocumented bugs across a dozen files with no test suite, then record what caused them.

Mostly Python and Go, with some Rust, C, and Ct+. A trajectory runs about 100 steps.

WHAT YOU JUDGE IN A TRAJECTORY

• Was the command right for the state the environment was actually in?

• Did the agent read the previous output correctly?

• Was the step wrong, or only inefficient — these are scored differently.

• Where did the run first go off course — usually earlier than where it visibly broke.

• Did the agent notice its own mistake and recover, or keep building on a false assumption?

• Did it game the grader instead of solving the task (e.g., weakening a test or hardcoding an expected value)?

WHAT WE NEED FROM YOU

• Experience — 2+ years in software engineering, DevOps, or site reliability, with real debugging in real codebases.

• Languages — Strong in Python or Go, and able to read a language you've never used.

• Linux — Comfortable with logs, running processes, build failures, and containers.

• Workflow — Everyday Git, diffs, pull requests, and issue tracking.

• Debugging — Able to work with no test suite and no error message pointing at the cause.

• Focus — Able to hold context across a long run, because step 74 can depend on step 12.

• Writing — Clear English, since every judgement needs an explanation another engineer can check.