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Founding AI Engineer (Application in Description)

OpenSesame

Toronto

On-site

CAD 80,000 - 100,000

Full time

Today
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Job summary

A leading company in Toronto is seeking a talented founding engineer to help build an AI-native agent for SaaS products. This role involves hands-on work with agent orchestration, prompt engineering, and deploying production-grade applications. Join a fast-paced environment where you'll work closely with co-founders and directly impact product development. Ideal candidates should have strong Python skills and experience with AI/ML systems.

Benefits

Brand-new work laptop (Mac)
Beautiful downtown office
Learning from strong investors and advisors

Qualifications

  • Experience building agentic workflows and LLM-integrated applications.
  • Ability to document technical decisions clearly.

Responsibilities

  • Own key pieces of agent infrastructure and improve performance.
  • Contribute to agent ecosystem and technical strategy.

Skills

LangChain expertise
Prompt engineering
Python
AI/ML system design
Docker
Understanding of RNNs

Tools

PyTorch
TensorFlow
GCP

Job description

We’re looking for a talented founding engineer to join us in person in Toronto.

At OpenSesame, we believe every product should be conversational by default. The next time someone opens a dashboard or tool, they shouldn’t feel lost; they should just be able to ask.

That’s what we’re building with Cell, our embedded AI agent.

What We’re Building

Cell can ingest any SaaS product’s APIs and turn it into a real-time, intelligent agent. We’re giving end users an AI-native way to explore, understand, and take action inside software, just by asking.

We’re starting with legacy SaaS verticals like construction tech, insurtech, logistics, and workforce management and helping them ship the Gen AI version of their products without starting from scratch.

This is a zero-to-one product. We’re building fast, shipping every week, and working directly with live customers.

What You’ll Work On

You’ll own key pieces of our agent infrastructure and be hands-on with:

  • Agent orchestration and execution frameworks
  • Tool selection, routing, and prompt optimization
  • Improving agent reliability and performance
  • Deploying new agent behaviors and testing in production
  • Contributing to our agent ecosystem and technical strategy
  • Working with co-founders daily to ship fast, learn fast, and push the product forward

You Should Have

  • LangChain expertise: experience building agentic workflows, retrieval-augmented generation (RAG) systems, and LLM-integrated applications
  • Strong prompt engineering skills, structuring prompts for context-aware, accurate outputs
  • Advanced Python skills, especially in AI/ML system design and backend development
  • Solid experience with PyTorch or TensorFlow for model development and deployment
  • Familiarity with GCP (Google Cloud), particularly AI Platform, Cloud Functions, and ML pipelines
  • Working knowledge of Docker for environment management and reproducible builds
  • Understanding of RNNs and sequence modeling concepts (useful in NLP/time series workflows)
  • Experience building and deploying production-grade LLM applications
  • Ability to document technical decisions clearly and work quickly in uncertain, zero-to-one environments

Compensation Range: 80K–$100K Salary + Equity

Bonus:

  • Brand-new work laptop (Mac)
  • Fully in-person in Toronto (we’re based out of a beautiful downtown office)
  • Backed by strong investors and advisors; you'll learn from them
  • You’ll be working alongside a team that deeply cares about product, design, and execution

Don't Apply if:

  • You want to be in a 9–5 environment
  • You prefer following a hundred Jira tickets
  • You don’t want an environment that is high-tempo, high-trust, and in-person

We’re looking for someone who wants to help define what AI agents become and build a real product around it.

Note: We're not a huge fan of resumes or GPT essays. Send us a Loom or quick DM. Show us what you’ve built or what you’re excited about. We care more about what you can do than your last job title.

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