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HC
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15Rock

Applied AI Engineer - Evaluation & Reliability

Toronto, ON, Canada
Greater Toronto Area, Canada, Canada

Full-time

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Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Apr 7, 2027
Posting language: English
Posted: Oct 9, 2026

Original job description

Applied AI Engineer - Evaluation & ReliabilityThe problem you'd own

15Rock is a financial intelligence firm. Our research goes in front of institutional investors and gets read line by line - by people looking for the one number that doesn't hold up. Every figure has to reconcile across every table and sentence; every claim has to trace to a live source.

We build that research with a multi-agent pipeline on large language models. LLMs write well and count badly: left alone, they produce clean prose that contradicts the table three paragraphs up. Our answer isn't "prompt harder." It's to route every number through deterministic computation and gate every report behind checks that pass or fail - never a model grading its own work. You'd build that layer.

What you'll build

Deterministic evaluation gates that block a report when a defect is present - measured against thresholds set before the run, not a gut feel.
A fact-reconciliation layer that verifies a figure agrees with itself everywhere it appears.
Citation-integrity checks: every reference resolves, every quote is real, every source is live.
Golden-set and regression harnesses that catch quality drift before it ships.
The path from research to production: hardening a validated approach into the pipeline, behind CI, with the traces to prove it works.

What we're looking for

You've shipped LLM systems to production - not demos - where being wrong had a cost.
You've built the evaluations that kept them honest: you think in precision and recall, and you define "good" before you measure it.
Strong Python; you can own backend services and data pipelines yourself.
You reason about the numbers, not just the tokens - enough quantitative or financial literacy to know when a figure is wrong, or the appetite to learn it fast.
Self-directing. You'd rather write a one-page memo than wait for a ticket.

Bonus: model-risk or evaluation-infrastructure work in a regulated setting; LangGraph, DuckDB, CI you owned; a finance or quantitative background.

This role is not

Prompt engineering, a pure research seat, or a place where "the model said so" is an answer.

How we work

A small, senior team with direct access to the founder and research lead. Async by default - we meet on blockers, not to read status aloud. We run on hypotheses and measurable outcomes.

Details

Downtown Toronto, on-site / hybrid. Must be authorized to work in Canada. Early-stage financial intelligence firm, recognized by the Globe and Mail Changemaker Award and selected for Google for Startups.

To Apply: send a short note and something you've built where correctness mattered to Careers@15Rock.com . Tell us about a check you built that caught something a person would have missed.

15Rock is an equal-opportunity employer.

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More about this job

Responsibilities

Build deterministic evaluation gates that block reports with defects, and develop checks for fact consistency, citation validity, and source integrity. Create golden-set and regression testing harnesses, then harden validated approaches for production with CI and traceable evidence.

Requirements

Candidates should have shipped production LLM systems where errors carried real costs and built evaluations using defined quality measures such as precision and recall. Strong Python skills and the ability to own backend services and data pipelines are required, along with quantitative or financial literacy or the ability to learn it quickly.

Skills

Python
LLM Production Systems
Evaluation Design
Precision and Recall
Deterministic Computation
Fact Reconciliation
Citation Integrity
Regression Testing
Backend Services
Data Pipelines
Quantitative Analysis
Financial Literacy
CI
LangGraph
DuckDB

Visa sponsorship

Not detected in the job text

Keywords

Applied AI
Large Language Models
Multi-Agent Pipeline
Python
Deterministic Computation
Evaluation Gates
Precision
Recall
Fact Reconciliation
Citation Integrity
Golden Sets
Regression Testing
Backend Services
Data Pipelines
Production Hardening
Continuous Integration
LangGraph
DuckDB
Model Risk
Evaluation Infrastructure
Financial Intelligence
Quantitative Analysis
Institutional Investors
Source Verification

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