Posted yesterday
Applied AI Engineer
@ Jobgether
Remote in Canada
Overview
Jobgether is hiring an Applied AI Engineer on behalf of a partner company based in Canada. The role builds and operates production AI infrastructure, including agent orchestration, retrieval-augmented generation, evaluation frameworks and safety controls. It is a full-time position within a small, senior founding engineering team.
Responsibilities:
- Build and operate AI runtime and agent orchestration infrastructure
- Design RAG, model routing and evaluation frameworks
- Implement guardrails and safety controls for production AI
- Partner with product teams and customers on AI use cases
Requirements summary:
- Experience shipping LLM or ML software to production users
- Systematic AI evaluation methods and quality assessment
- Treat cost and latency as core engineering constraints
- Clear communication of technical trade-offs
Source and dates
Employer career site / ATS feed · lever
- Employer posting date
- 2026-11-05
- First seen by our source
- 2026-11-05
- Source record updated
- 2026-11-05
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Senior |
| Department | Software development |
| Hours per week | 40 (estimated) |
| Work setting | Office, Home |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
Summary and details written by AI from the posting; the employer’s posting is the authority.
Jobgether
Saved company profile
Historical company information from a saved The Jobs API profile (LinkedIn/Crunchbase fields). It is not live-verified; figures may have changed. Missing values remain unknown.
Your career navigator for remote work.
Full company description
Jobgether is an AI-powered career coach and matching platform fixing the broken job search. Remote professionals no longer waste hours applying blindly; instead, they receive a personalized job search strategy, stronger visibility, and curated matches aligned with their skills, flexibility preferences, and career goals. We flip the hiring model by connecting talent only to roles that truly match, reducing noise for employers and eliminating wasted effort for candidates. Jobgether combines AI coaching, profile optimization, Match Score insights, and the world’s largest remote job database to help people land opportunities faster and with less bias. Our purpose is to make remote job search guided and intentional. Our mission is to become the world’s reference platform for remote talent, ensuring no professional remains invisible and every match is meaningful.
- LinkedIn followers
- 1,498,314
- People associated on LinkedIn
- 391
- Reported office locations
- Brussels, BE
- Business categories
- Internet
- Virtual Workforce
- Other recorded names
- Jobgether
- Profile identifies a recruitment agency
- No
- Reported total investment
- 2,557,655
Currency and observation date were not supplied; this is not a current valuation or a funding round.
Jobgether is an AI-powered career coach and matching platform fixing the broken job search. Remote professionals no longer waste hours applying blindly; instead, they receive a personalized job search strategy, stronger visibility, and curated matches aligned with their skills, flexibility preferences, and career goals. We flip the hiring model by connecting talent only to roles that truly match, reducing noise for…
| Field | Value |
|---|---|
| Industry | Internet Marketplace Platforms |
| Company size | 11-50 employees |
| Headquarters | Brussels |
| Organization type | Privately Held |
| Year founded | 2020 |
| Open jobs on Jobsy | 400 |
| View page |
This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for an Applied AI Engineer based in Canada.
As an Applied AI Engineer, you will build and operate the core AI infrastructure that powers reliable, secure, and scalable AI features in production environments. You will focus on AI runtime architecture, agent orchestration, retrieval-augmented generation (RAG), evaluation frameworks, and safety controls. Working with proven commercial models, you will turn advanced AI capabilities into practical solutions that support mission-critical customer workflows. You will join a small, senior founding engineering team and help establish its technical standards, development practices, and evaluation discipline. The role combines hands-on engineering with close collaboration across product teams and customers. You will have the opportunity to shape a growing AI platform while ensuring that performance, cost, reliability, and measurable business value remain central to every delivery.
Accountabilities:
Build and operate the AI runtime, tool-calling capabilities, and orchestration infrastructure required for production agent workflows.
Design model selection and routing strategies, balancing performance, latency, and operating costs.
Implement and improve retrieval-augmented generation (RAG), grounding, and context-retrieval systems where they demonstrably improve output quality.
Develop evaluation harnesses, golden datasets, and quality benchmarks to assess model and agent performance, support release decisions, and identify regressions or performance drift.
Establish evaluation frameworks for AI quality and implement guardrails and safety controls, treating retrieved information and tool outputs as untrusted inputs.
Take ownership of production AI behaviour, including reliability, latency, cost, and failure management.
Collaborate with product teams to determine when agent-based solutions are appropriate and when alternative approaches will deliver better results.
Partner with customers and product stakeholders to validate outcomes, identify valuable use cases, and prioritize development based on measurable impact.
Apply an iterative, value-driven approach by proving the value of focused solutions before scaling successful implementations.
Instrument AI systems and measure their impact, using evidence and performance data to guide product and engineering decisions.
Integrate automated quality assurance, testing, quality gates, and regression checks into development and delivery pipelines.
Help establish engineering standards and evaluation and safety practices across the team, while contributing to technical interviews, mentoring, and future team growth.
Promote a culture of technical excellence, customer focus, pragmatic decision-making, and effective collaboration with product teams across the organization.
Demonstrated experience shipping software powered by large language models (LLMs) or machine learning (ML) to real production users, beyond prototypes, demonstrations, or experimental notebooks.
Strong understanding of AI evaluation methods and the ability to assess model and agent quality systematically rather than relying solely on prompt experimentation.
Ability to treat cost and latency as fundamental engineering constraints when designing and delivering AI-powered systems.
Clear communication skills, with the ability to explain technical decisions and trade-offs to engineers, product stakeholders, and customers.
A pragmatic, outcome-oriented mindset, with the ability to prioritize work based on customer needs, measurable value, and practical delivery considerations.
Strong engineering judgment and the ability to make informed decisions about where AI agents are appropriate and where simpler solutions are more effective.
Experience building and operating production-grade AI agents or RAG systems, including understanding their operational challenges and failure modes.
Experience implementing model routing strategies or delivering measurable reductions in AI infrastructure and operating costs.
Experience building evaluation harnesses that inform release decisions, including LLM-as-a-judge approaches calibrated against human assessments.
Familiarity with model fine-tuning, distillation, or other model optimization techniques.
Strong programming skills in Python or C#/.NET.
Experience grounding AI applications in structured, well-modeled business data.
Background in system and platform architecture, including the ability to evaluate technical trade-offs and long-term implications.
Experience developing or operating enterprise-scale software, with an understanding of reliability, security, and integration requirements.
Productive use of AI-assisted coding tools, with the technical judgment to review, validate, and supervise their output.
Opportunity to join a founding AI engineering team and help shape the platform's architecture, technical standards, and future development.
Meaningful ownership of production AI systems supporting mission-critical customer workflows.
Close collaboration with experienced engineering and product professionals across multiple teams.
Opportunity to influence AI strategy, evaluation practices, safety standards, and team development.
Exposure to practical applications of commercial AI models, agent orchestration, retrieval systems, and enterprise-scale software challenges.
Requirements:
The following experience is considered an advantage, but is not required:
Benefits:
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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