Founding AI Engineer (Application in Description)

ZipRecruiter; Toronto; On-site; CAD 80,000 - 100,000; Full time

Job summary

A leading company in Toronto is seeking a passionate founding engineer to develop an AI-powered agent for SaaS products. This role involves hands-on work with agent orchestration, prompt engineering, and backend development. Join a fast-paced team focused on innovation and direct customer interaction, contributing to a zero-to-one product environment.

Benefits

Brand-new work laptop (Mac)

Beautiful downtown office

Backed by strong investors and advisors

Qualifications

• Experience building agentic workflows and LLM-integrated applications.
• Strong prompt engineering skills for context-aware outputs.
• Advanced Python skills focused on AI/ML system design.

Responsibilities

• Own key pieces of agent infrastructure and improve performance.
• Deploy new agent behaviors and test in production.
• Work with co-founders to push the product forward.

Skills

LangChain expertise

prompt engineering

Python

PyTorch

TensorFlow

GCP

Docker

RNNs

Job description

Job Description

Actual Application: https://ljc0du9aaju.typeform.com/to/R9xmAJ37

We’re looking for a passionate 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-powered 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, 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
• Building internal debugging and evaluation tooling
• 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 (RAG) systems, and LLM-integrated applications
• Strong prompt engineering skills, structuring prompts for context-aware, accurate outputs
• Advanced Python skills, focusing on AI/ML system design and backend development
• Solid experience with PyTorch or TensorFlow for model development and deployment
• Familiarity with GCP (Google Cloud), especially 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 efficiently 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, from whom you’ll learn
• You’ll work alongside a team that cares deeply about product, design, and execution

Don't Apply if:

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

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

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