Senior Software Engineer

Posted Yesterday
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Toronto, ON, CAN
Hybrid
Senior level
Artificial Intelligence • Marketing Tech • Software • SEO
The Role
Lead design and implementation of production AI/LLM systems and scalable FastAPI backends, implement embedding-based semantic search with PostgreSQL/pgvector, build WebSocket real-time collaboration, own GCP/Kubernetes infrastructure (KEDA, Terraform), and mentor engineers while driving architectural decisions and feature rollouts.
Summary Generated by Built In
About Us

The search bar is becoming a conversation. Brands need to know how to get found by AI, and that's what we do. Yolando is the platform that helps marketers understand and improve how AI models discover, cite, and recommend their brand.

We've raised $8.5M from Drive Capital and MaRS Discovery District. We're 15 people building the standard for Generative Engine Optimization.

Role Overview

We are looking for a Senior Software Engineer to drive the technical direction of Yolando, our flagship AI Search Optimization platform. You will own AI/LLM systems end-to-end, designing production agents using Pydantic AI for content generation and competitive intelligence. As a technical leader, you will architect scalable backend services using FastAPI and PostgreSQL, build real-time collaborative systems with WebSockets, and mentor engineers to establish patterns that scale.

Key Responsibilities
  • Own AI/LLM Systems End-to-End: Design and build production AI agents using Pydantic AI for content generation, brand analysis, and competitive intelligence. Implement tool-based architectures that enable agents to explore signals and generate recommendations at scale.

  • Architect Scalable Backend Services: Build and evolve FastAPI microservices that power real-time content workflows, handling complex state machines for onboarding, content generation, and recommendation pipelines. Optimize PostgreSQL with pgvector for embedding-based semantic search and deduplication.

  • Build Real-Time Collaborative Systems: Implement WebSocket-based real-time collaboration features, including document synchronization, streaming AI responses, and live status updates using technologies like Yjs CRDTs.

  • Drive Infrastructure Excellence: Own service deployment on GCP/Kubernetes with KEDA event-driven autoscaling. Design ScaledJobs for background processing, implement zero-downtime migrations, and establish observability patterns with Logfire.

  • Lead Technical Direction: Mentor engineers, drive architectural decisions, and establish patterns that scale. Own complex features from design through production rollout, coordinating across frontend and data engineering teams.

What We're Looking For
  • 5+ years backend engineering with Python and production experience with FastAPI or similar async frameworks.

  • Proven track record building AI/LLM-powered applications in production (prompt engineering, agent architectures, tool use patterns).

  • Deep experience with PostgreSQL, including query optimization, indexing strategies, and migrations at scale.

  • Strong understanding of distributed systems: event-driven architectures, background job processing, caching patterns.

  • Experience with GCP, Kubernetes, and Terraform for production infrastructure.

  • Track record of technical leadership: mentoring, architectural decision-making, cross-team coordination.

  • Ownership mindset: you drive features end-to-end, from design through production support.

Bonus if you have:
  • Experience with vector databases (pgvector, Pinecone) and embedding-based search/RAG systems.

  • Background in real-time systems: WebSockets, CRDTs, collaborative editing.

  • Familiarity with Pydantic AI or similar structured LLM frameworks.

  • Experience with KEDA or other event-driven autoscaling patterns.

  • Background in SEO, content marketing, or marketing technology.

Our Stack
  • Backend: Python 3.11, FastAPI, SQLModel, PostgreSQL/pgvector, Pydantic AI, Redis

  • Frontend: Next.js 14+ (App Router), React 19, TypeScript, Plate.js, Radix UI

  • Infrastructure: GCP (Cloud Run, Pub/Sub, AlloyDB), Kubernetes, KEDA, Terraform, GitHub Actions

  • Observability: Logfire, PostHog

  • Data: Databricks, Protocol Buffers, Alembic migrations

Why Join Us?
  • Join an innovative, fast-growing startup building cutting-edge AI marketing solutions.

  • Make a meaningful impact by shaping the platform's user experience, design identity, and overall success.

  • Dynamic environment with opportunities for real ownership, learning, and growth.

  • Competitive salary and support for professional development.

How to Apply
  • Please send your resume and a brief note about why you're interested in joining us.

  • We'd love to see your work and hear your story!

  • This is a hybrid role, with 4 days per week in our downtown Toronto office.

Skills Required

  • 5+ years backend engineering experience
  • Production experience with Python
  • Production experience with FastAPI or similar async frameworks
  • Proven track record building AI/LLM-powered applications in production (prompt engineering, agent architectures)
  • Deep experience with PostgreSQL including query optimization, indexing, and migrations at scale
  • Strong understanding of distributed systems, event-driven architectures, background job processing, and caching patterns
  • Experience with GCP, Kubernetes, and Terraform for production infrastructure
  • Technical leadership experience: mentoring, architectural decision-making, cross-team coordination
  • Ownership mindset: drive features end-to-end from design to production support
  • Experience with vector databases or embedding search (pgvector, Pinecone)
  • Experience with real-time systems (WebSockets, CRDTs, collaborative editing)
  • Familiarity with Pydantic AI or similar structured LLM frameworks
  • Experience with KEDA or event-driven autoscaling patterns
  • Background in SEO, content marketing, or marketing technology
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The Company
30 Employees

What We Do

Yolando is a SaaS platform that helps marketing teams optimize their brand's visibility and representation across AI platforms. By focusing on Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO), Yolando analyzes AI-generated responses and provides actionable recommendations and content strategies to improve how brands are cited and perceived by large language models like ChatGPT, Gemini, and Claude.

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