Founding Engineer

Department: Engineering

Location: Toronto (Canada), San Francisco, Remote (US and Canada)

Employment Type: FullTime

Founding Engineer

tl;dr: We’re hiring our first few engineers to help scale Keplar Voice from early traction to breakout growth. You’ll work directly with our CEO and founding team to solve some of the most interesting and challenging problems in software today—deploying GenAI at scale, building novel voice interfaces, running applied R&D experiments with leading ML models, and shaping a product that’s redefining how enterprises learn about their customers. This is a high-ownership, high-impact role for someone excited to bet on a career-defining opportunity at a fast-moving, venture-backed startup.

About Keplar

Keplar is an AI-powered market research platform that enables companies to conduct qualitative research at quantitative scale. Using advanced voice AI and automated analysis, Keplar helps businesses have natural conversations with hundreds of customers simultaneously, transforming months of research into hours of insights.

Founded in 2022 and backed by Kleiner Perkins, SV Angel, and other leading investors, Keplar serves Fortune 500 companies across multiple industries. For more information, visit www.keplar.io.

We’re reinventing market research, insights, and customer understanding — a critical but underserved part of business — which directly impacts innovation, marketing, and positioning for iconic brands.

Why Keplar Voice

• Explosive growth: We’re seeing traction across mid-market and enterprise, including six-figure deals and high-velocity sales cycles.

• Product-market fit: We close at a high rate, and most deals are driven by real customer pain—meaning we rarely compete on price.

• A viral product: Insights are easy to share across entire organizations, creating a natural product-led growth loop.

• Elite team: Our founding team comes from Research at Google, Engineering at Meta and Amazon, and growth at Samsara — we have deep expertise scaling enterprise and product-led SaaS companies.

• Massive market: The customer understanding market is huge, with growing demand for tools that help run end-to-end workflows and deliver high quality customer insights with speed and scale.

What You’ll Do

As a founding engineer, you’ll own core parts of the product stack and help chart the technical direction of the company. Expect to work across fullstack engineering, research, infrastructure, and product, with impact that’s visible from day one.

• Push the boundaries of applied GenAI: Deploy foundation models for dynamic, 1-1 human conversations, reasoning, and thematic analysis at scale.

• Voice & Speech AI: Advance our pipeline for voice generation, speech recognition, and real-time conversation orchestration.

• Full-stack product development: Build features that make research faster and more intuitive for end-users — from insights dashboards to collaboration tools.

• Push the boundaries of agent-led UX: Keplar’s backend is agent-led, meaning that users access many of our features by talking to an agent. Build the future of agent-led UX and lead experiments with generative UI.

• Scale infrastructure: Design systems that reliably run thousands of AI-mediated interviews concurrently, manage growing datasets, and integrate securely into enterprise workflows.

• Shape the foundation: Establish engineering best practices, mentoring early hires, and contributing to a culture of speed, rigor, and craftsmanship.

• Close the loop: Work closely with Growth and Customers to bring product feedback into the roadmap, ensuring we’re building the right things at the right time.

What We’re Looking For

• 5+ years of full stack software engineering experience, ideally with exposure to ML/AI products or infrastructure.

• Experience shipping production systems in a fast-paced startup environment (0→1 or 1→10).

• Strength in one or more of: backend systems, ML/AI pipelines, full-stack web, real-time/voice infrastructure.

• Curiosity and ability to go deep in applied R&D areas like LLMs, voice generation, speech recognition, and reasoning models.

• High energy builder mindset that biases for action. Excitement for ambiguity. There’s lots to build and lots we don’t know. Let’s learn and grow together!

• Bonus: prior experience with enterprise SaaS, research/insights tools, or scaling products with heavy data/compute requirements.

Compensation

This is a full-time role with competitive salary + meaningful early-stage equity. You’ll be joining at the ground floor, with the ability to shape both product and culture.

We want this to be the rewarding role of your career.

Next Steps

If you’re ready to tackle some of the most exciting problems in AI and help define the future of enterprise research, we’d love to meet you.