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Added 28 mins ago
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KoraHome.ai

AI Engineer - Agents & Backend

Toronto, ON, Canada
Greater Toronto Area, Canada, Canada

Job type: Full-time
Apply by: Mar 26, 2027
Posting language: English
Posted: Sep 27, 2026

Apply About employer

Applications open in a new tab.

Original job description

About Kora

Kora is a Toronto-based, VC-backed startup building an intelligent assistant for busy families. Our product combines a mobile app with a dedicated smart home display to help families manage schedules, chores, shopping, meals, and everyday responsibilities.

We are building an assistant that understands family context, remembers what matters, anticipates what needs attention, and takes action to help families get things done.

We are a small, hands-on team. You will work directly with the founders to build Kora’s core intelligence and shape how the assistant behaves in everyday life.

The role

We are looking for an AI engineer with strong backend development skills to build and improve Kora’s core assistant capabilities.

You will work on the full agent loop: understanding a request, gathering relevant context, deciding what to do, calling tools, checking results, and following through. Your work will include prompts, orchestration, memory, integrations, evaluations, and the services that run these workflows.

You should enjoy turning emerging AI capabilities into useful product features and making them dependable enough for real users.

What you’ll build

Agent reasoning and execution: The prompts, tool definitions, control flow, and execution harness that enable Kora to complete tasks across multiple steps.
Family context and memory: Systems that help Kora understand people, preferences, schedules, responsibilities, and ongoing commitments.
Proactive assistance: Workflows that detect changes, conflicts, preparation needs, and deadlines, then decide when and how to help.
Tools and integrations: Connections to calendars, tasks, shopping lists, email, and other services that let the assistant take action.
Conversational experiences: Support for requests through chat, voice, images, and forwarded information.
Reliable backend infrastructure: APIs, background jobs, event processing, and persistent workflow state.
Evaluation and observability: Tools to understand agent behavior, measure quality, investigate failures, and improve performance.

What you’ll do

Own AI features from initial design and prototype through production deployment and iteration.
Develop and refine system prompts, context assembly, structured outputs, and tool-calling behavior.
Build Python backend services that connect models, application data, and external integrations.
Design workflows that can handle missing information, interruptions, retries, and partial failures.
Implement permissions and confirmation flows so the assistant acts appropriately on a family’s behalf.
Build evaluations using realistic scenarios and production failure cases.
Investigate agent traces and user feedback to identify why a workflow succeeded or failed.
Improve response quality, latency, and inference cost.
Collaborate with mobile and device engineers to deliver a consistent assistant experience.
Help decide when to use an LLM, a deterministic workflow, or a combination of both.

What we’re looking for

Strong Python skills and experience building backend services, APIs, and database-backed applications.
Hands-on experience building an LLM-powered application beyond a basic tutorial.
Practical understanding of prompting, tool calling, structured outputs, context management, and retrieval.
Experience shipping software and diagnosing problems in production.
Ability to reason about asynchronous tasks, application state, error handling, and data consistency.
A systematic approach to testing AI behavior and evaluating whether changes actually improve the product.
Product judgment: you care about whether the assistant solves the user’s problem and earns their trust.
Regular use of AI development tools, with ownership of the quality and correctness of the resulting code.
Comfort working independently in a small team, clarifying ambiguous problems, and delivering complete features.

Helpful experience

Production AI agents or workflows that execute actions through external tools.
Agent memory, context engineering, retrieval systems, or knowledge graphs.
Durable workflows, job queues, scheduling, and event-driven systems.
PostgreSQL, Firebase, GCP, or similar infrastructure.
OAuth and integrations with calendar, email, or productivity services.
Voice assistants, real-time streaming, or multimodal applications.
Agent evaluations, tracing, monitoring, and regression testing.
Handling untrusted inputs, prompt injection, and permissions in AI applications.

We value strong engineering fundamentals, practical judgment, and evidence of building useful things. You do not need experience with every framework or technology listed.

Why join Kora

Build the core intelligence of a consumer AI product.
Work directly with the founders and influence architecture and product behavior.
Tackle real problems involving memory, reasoning, proactive assistance, and action.
Connect AI capabilities to mobile software and a physical product in people’s homes.
Take substantial ownership and grow with an early-stage, VC-backed company.

How we work: AI-native from day one

Kora is a fully AI-native company. AI coding agents are central to how we research, build, debug, test, and ship software. We expect every engineer to work effectively with tools such as Cursor, Claude Code, Codex, or equivalent platforms.

You must be able to:

Use agentic coding workflows to deliver complete features, from planning and implementation through testing and review.
Give coding agents clear context, break complex problems into manageable tasks, and guide their work across an existing codebase.
Use AI tools to investigate bugs, explore unfamiliar code, refactor systems, and automate repetitive development tasks.
Critically review generated code, verify its behavior, and take responsibility for correctness, security, and maintainability.
Continuously improve your development workflow as tools and capabilities evolve.

We look for practical experience using coding agents to ship working software, alongside the engineering judgment to recognize when their output needs correction.

How to apply

Send your résumé or LinkedIn profile and a short description of an AI application or backend system you have built. Tell us what you personally owned, one difficult problem you encountered, and how you solved it.

Demos, GitHub repositories, and technical write-ups are welcome. If your work is confidential, a description of your contribution is enough.

Apply About employer

More about this job

Responsibilities

Build and operate Kora’s AI assistant workflows, including agent reasoning, memory, proactive assistance, integrations, and reliable backend services. Own AI features from design through production, evaluating and improving their quality, reliability, latency, and cost while collaborating with mobile and device engineers.

Requirements

Candidates should have strong Python backend skills and hands-on experience building and shipping LLM-powered applications, including prompting, tool calling, context management, and retrieval. They should be able to design reliable asynchronous workflows, evaluate AI behavior, diagnose production issues, use AI coding agents effectively, and take ownership of product quality.

Skills

Python
Backend Development
API Development
LLM Applications
Prompt Engineering
Tool Calling
Context Management
Retrieval
Agent Orchestration
Database-Backed Applications
Asynchronous Workflows
AI Evaluation
Production Debugging
PostgreSQL
OAuth Integrations
AI Coding Agents

Visa sponsorship

Not detected in the job text

Keywords

Python
LLM
AI Agents
Backend Services
APIs
Prompt Engineering
Tool Calling
Structured Outputs
Context Assembly
Agent Memory
Retrieval Systems
Knowledge Graphs
PostgreSQL
Firebase
Google Cloud Platform
OAuth
External Integrations
Background Jobs
Job Queues
Event-Driven Systems
Durable Workflows
Voice Assistants
Multimodal Applications
Agent Evaluations
Observability
Regression Testing
Prompt Injection
Permissions
Cursor
Claude Code

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