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Added 4 mins ago
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Added 33 mins ago
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Closed listing

Jobright.ai

Prompt Engineer - Early Career (Canada)

Canada

Job type: Full-time
Experience: Recent graduate or early-career professional (0–2 years of experience) with a degree in Computer Science, Linguistics, Cognitive Science, or a related field
Posting language: English
Posted: Sep 26, 2026

This opening has closed.

The original listing is kept below for reference.

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Original job description

Archived listing. The details below describe a past opening.

Jobright is your personal AI job search agent transforming the job search process. They are seeking an early-career Prompt Engineer to craft and evaluate prompts that enhance the performance of AI outputs across user-facing features.

Why Join Us

Build real, production AI agents used by real users

High ownership and impact

Work at the intersection of AI, agents, and product

Shape how people experience AI-driven job search

Responsibilities

Craft, test, and iterate on prompts and prompt chains that drive the quality and reliability of AI agent outputs across user-facing features

Develop systematic evaluation frameworks to measure prompt performance against metrics like accuracy, consistency, tone, and hallucination rate

Investigate failure modes and edge cases in model responses, diagnose root causes, and design prompt-level fixes that scale across use cases

Maintain a versioned prompt library with clear documentation, so the team can track what changed, why, and how it performed

Work closely with product and engineering teams to translate ambiguous user needs into structured instructions that LLMs can follow reliably

Qualification

Required

Recent graduate or early-career professional (0–2 years of experience) with a degree in Computer Science, Linguistics, Cognitive Science, or a related field

Deep curiosity about how LLMs interpret and respond to instructions, and an intuitive sense for why small wording changes can produce dramatically different outputs

Proficiency in Python for scripting evaluation pipelines, parsing model outputs, and running batch prompt experiments at scale

Exceptional written communication skills - the ability to write instructions that are precise, unambiguous, and robust to misinterpretation

Preferred

Previous experience designing prompts for production applications, not just casual ChatGPT usage - understanding the difference between a prompt that works once and one that works at scale

Familiarity with techniques like few-shot prompting, chain-of-thought, self-consistency, and retrieval-augmented generation

Hands-on exposure to evaluation tooling or building custom scoring rubrics to grade model outputs beyond simple pass/fail

A genuine obsession with language - the kind of person who notices when a comma changes the meaning of a sentence

About employer

More about this job

Responsibilities

Create, test, and refine prompts and prompt chains for reliable AI agent outputs, and build evaluation frameworks to measure accuracy, consistency, tone, and hallucination rates. Investigate response failures, maintain a documented versioned prompt library, and collaborate with product and engineering teams to turn user needs into clear instructions for language models.

Requirements

Applicants should be recent graduates or early-career professionals with 0–2 years of experience and a degree in Computer Science, Linguistics, Cognitive Science, or a related field. Required qualifications include Python proficiency, strong written communication, and curiosity about how language models interpret instructions; production prompting, evaluation methods, and related techniques are preferred.

Skills

Prompt Engineering
Prompt Evaluation
Python
Large Language Models
Prompt Chains
Evaluation Frameworks
Model Output Analysis
Failure Mode Analysis
Written Communication
Few-Shot Prompting
Chain-of-Thought
Self-Consistency
Retrieval-Augmented Generation
Scoring Rubrics
Prompt Documentation

Visa sponsorship

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Keywords

Prompt Engineering
Prompt Chains
Large Language Models
AI Agents
Python
Evaluation Frameworks
Prompt Performance
Accuracy
Consistency
Tone
Hallucination Rate
Failure Modes
Edge Cases
Prompt Library
Version Control
Few-Shot Prompting
Chain-of-Thought
Self-Consistency
Retrieval-Augmented Generation
Evaluation Tooling
Scoring Rubrics
Batch Experiments
Model Output Parsing
Production Applications
Software Development

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