Replicant

Senior Software Engineer in Test

Canada, CanadaFull timeSeniorPosted 12 days ago
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At Replicant, we believe AI should work for people, starting with customer service. We’re looking for a Software Development Engineer in Test (SDET) to help raise the bar for quality across our voice AI platform as we continue to scale. This person will play a key role in shaping how quality is defined, measured, and built into the product experience from the start — across platform capabilities, AI agents, customer configurations, integrations, and release workflows. This is an opportunity to help build the systems, standards, and tooling that make quality a durable advantage for both our customers and our teams.

As a SDET you will partner closely with Engineering, Product, and Delivery to create a more unified and scalable approach to quality. You’ll define standards, improve testing strategy, build and evolve automation and platform-level tooling, and turn customer and product insights into better validation systems. This is a hands-on engineering role for someone who is excited to work at the intersection of software quality, automation, analytics, and AI. The right person will help us move toward a modern quality engineering practice where testing is proactive, automated wherever possible, and grounded in the realities of conversational AI.

What You'll Do

- Act as a senior technical authority for quality engineering at Replicant; shaping how quality is built into the platform through hands-on engineering, championing a high bar across teams, and driving the practices and execution that make it real.

- Raise the technical bar across our team of AI-enabled QA Engineers through hands-on example, code and test review, pairing, and mentorship; leveling up how a small team builds a scalable quality engineering practice.

- Help drive Replicant's AI-native quality engineering strategy to scale coverage, accelerate validation, and surface failures earlier.

- Build AI-driven testing workflows that let a small team deliver broad, scalable validation across th...