Syndio is the leading pay governance and compensation intelligence platform. We help organizations make better pay decisions at every stage of the compensation lifecycle, from leveling and offers to promotions and merit. Our platform gives HR, compensation, and finance leaders the data and decision support they need to govern pay fairly, compliantly, and with confidence. Wepartner with many of the world's most recognized and respected enterprises, helping them implement leading-edge compensation solutions with expert guidance and analyzing pay for over 10 million employees across the world. Join us in our mission to help companies make smarter pay decisions they can trust Essentials is our pay equity product, and its analyses are relied on for high-stakes decisions. Delivering that means running complex statistical work across datasets that routinely reach hundreds of thousands of records, fast enough that a customer can iterate on a real question instead of waiting overnight for a job to finish. You'll work on the workflows that move large datasets through ingestion, validation, modeling, and reporting: making them performant, making them observable, making them resilient when a single customer's dataset is an order of magnitude larger than anyone planned for. We are investing heavily in AI agents across the company, and Essentials is one of the highest-leverage places to apply them. You'll build the tooling that lets our agents carry out Essentials workflows — the harnesses, the guardrails, the context, and the evaluation that make an agent's output something we can stand behind, building on the AI capabilities our AI team provides. High-Performance Data Workflows Own performance end to end: query plans and indexing in Postgres, batching and parallelism, memory behavior, caching strategy with Redis,



and the difference between an algorithm that's clever and one that's actually fast on real customer data. These results carry real consequences for our customers — performance work that quietly changes an output is worse than no performance work at all. Long-running multi-stage pipelines fail in the middle; Build the tooling that lets our agents execute Essentials workflows: data validation and remediation, analysis setup, exception triage, report generation, and the long tail of work that currently requires a human to babysit it. Give agents the context they need to be productive across a large codebase: documentation, schemas, conventions, and project state that stay current. Partner with the Engineering Manager and technical leaders to set standards for testing, performance, and agentic practice — and hold the line on them. Deep experience in complex, distributed, service-based systems — you're comfortable reasoning about failure modes, data consistency, and latency across service boundaries, not just within one service. Proven performance and scale work. Experience with large-dataset computation, numerical or statistical workloads, or heavy data pipelines is exactly what we're after. Python, Go, Node/JavaScript, TypeScript, React, Postgres, and NoSQL stores such as Firebase. Testing as a first-class skill. Strong end-to-end and integration testing of service-based architectures,



with hands-on experience in an e2e framework (Playwright, Cypress, or similar) and a point of view on how to test systems where the interesting bugs live between the services. You use coding agents daily, you tune how you use them, and you build the harnesses that make them reliable — tight test loops, strong CI/CD gates, spec-to-code workflows, and ways of working that produce high-quality output rather than plausible-looking output. You can take an ambiguous, high-stakes problem and drive it to a shipped result without being managed through it. You work well across teams and with non-technical leaders, and you can translate technical constraints into business language without dumbing it down. You partner with technical leaders to establish standards across the team, and then live by them publicly. Hands-on experience building with AI systems — LLM applications, agent frameworks, retrieval, evaluation harnesses, or model-backed pipelines in production. This is a robust asset for this role. Background in statistics, data science, or quantitative analysis — regression modeling in particular. You like building products people depend on, and you care about the experience of whoever's on the other end — not just whether the pipeline ran. You've worked with sensitive data and treat security, privacy, and compliance as part of your job rather than someone else's. You've seen customer onboarding up close and know the ways cross-system data flows go wrong in practice. You're comfortable in unfamiliar territory — reading a third-party API's docs, tracing a bad record back through a pipeline, and working out what actually happened. You want a say in where the platform goes over the long term,

📌 Staff Software Engineer (Calgary)
🏢 Syndio
📍 Calgary