AI Engineer, Agents & Search
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 2d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 10d ago
The date the source published, not the day we noticed it (2026-09-22). Last seen at its source 1h ago.
We have tracked this listing since 22 Sep 2026 (9 days). The employer's own board has carried it every time we have read it, most recently 1 hour ago.
Is it remote?
The listing says yes
The location field doesn't say remote, so our assessment is based on the title or the description. Read the listing before applying.
Who may apply?
LATAM
The description agrees: it names United States, LATAM.
What the ad says
…Location: Remote — United States or Latin America US compensation: $17…
Pay
$170k–230k/yr
Read out of the job description by us, not from a structured field. Shown in the posting's own currency and period; we never convert.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
ashby employer's own board first seen 9d ago · last seen 1h ago
The listing
Employment: Full-time, direct hire
Location: Remote — United States or Latin America
US compensation: $170,000–$230,000+ annual base, depending on experience and scope. Flexibility toward the higher end for the right staff-level engineer.
LATAM compensation: A separate, lower regional range applies and will be discussed during the recruiting process.
About our Client
Our client builds AI-powered software for healthcare staffing. Its platform helps recruiters find healthcare providers, personalize outreach, manage ongoing conversations, and connect interested providers with relevant opportunities.
About the role
Our client is looking for an AI Engineer to build and operate production agent systems, with a focus on agent orchestration, search, retrieval, and evaluation.
You’ll develop the backend systems that allow agents to use tools, retrieve relevant information, maintain state, and complete workflows reliably. You should be comfortable taking systems from implementation through production operation and using repeatable evaluations to determine whether changes actually improve results.
What you’ll do
Build and improve production LLM agents and the orchestration layer that controls their execution.
Design tool-calling systems, including tool interfaces, validation, error handling, and recovery.
Develop retrieval pipelines combining structured filters, keyword search, embeddings, and reranking.
Build repeatable evaluations and experiments to measure agent behavior, retrieval quality, and regressions.
Implement durable, asynchronous workflows that handle retries, interruptions, and long-running tasks.
Investigate production failures and improve reliability, latency, cost, and observability.
Apply strong backend engineering practices to AI features used in real recruiting workflows.
What we’re looking for
Hands-on experience building, deploying, and operating LLM agent systems used in production.
Strong backend engineering fundamentals, with TypeScript experience or proficiency in an equivalent backend language.
Practical experience designing agent orchestration or harnesses, including execution control, state management, and tool use.
Experience with RAG or search systems and an understanding of how filtering, keyword retrieval, embeddings, and reranking work together.
Experience building repeatable evaluations, comparing approaches, and identifying meaningful improvements.
Experience with asynchronous processing and reliable workflows.
Ability to explain architectural decisions, production failures, and the trade-offs behind your solutions.
Nice to have
Experience in healthcare, staffing, recruiting technology, or related workflows.
Staff-level technical ownership across architecture, delivery, and production operation.
Experience improving both retrieval quality and downstream agent task completion.
Interview process
Resume review → G2i video screen for external applicants → direct technical fit review by Fetch → interviews focused on production agent systems, orchestration, tooling, and evaluation.
Target start: Before December.