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Engineering Lead

  • Toronto, ON, Canada

Full-time

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Job details

Job type
Full-time
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Posting language
English
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Original job description

About Docufy AI

Docufy AI is an AI-native document intelligence platform transforming how enterprises understand, automate, and manage complex documents. We leverage Large Language Models, agentic AI, retrieval systems, and intelligent workflows to help organizations accelerate operations while maintaining enterprise-grade security and compliance.

Our founding team has deep experience building enterprise software and AI products. We're backed by experienced operators and are actively scaling our platform, customers, and engineering organization.

The Opportunity

We're looking for a Engineering Lead for the technical evolution of Docufy AI.

This is not a traditional management role. You'll be the senior engineering leader responsible for architecture, product execution, AI platform development, and building a world-class engineering organization alongside the founders.

Initially, you'll spend the majority of your time writing code, designing systems, reviewing architecture, and mentoring engineers. Over time, you'll hire and scale the engineering team as the company grows.

What You'll Own
  • Own the overall technical architecture and engineering roadmap.

  • Lead development of AI-powered document intelligence products.

  • Design scalable cloud-native infrastructure and backend systems.

  • Build reliable LLM pipelines, Agentic workflows, RAG, and orchestration services.

  • Improve platform reliability, security, observability, and performance.

  • Partner closely with Product, Design, and Customer Success.

  • Recruit, mentor, and grow a high-performing engineering team.

  • Establish engineering best practices, development standards, CI/CD, testing, and release processes.

  • Support enterprise customer implementations and technical due diligence during fundraising.




Requirements

Technical Experience

We're looking for someone with experience across many of the following:

AI & Machine Learning


  • Large Language Models (OpenAI, Anthropic, Gemini, open-source models)

  • Agentic AI systems

  • Retrieval-Augmented Generation (RAG)

  • Vector databases

  • Prompt engineering

  • Evaluation frameworks

  • AI observability

  • Model orchestration frameworks (LangGraph, LangChain, LlamaIndex, etc.)


Backend Engineering


  • Python

  • FastAPI or similar frameworks

  • REST APIs

  • Event-driven architectures

  • Distributed systems

  • PostgreSQL

  • Redis

  • Background job processing


Cloud & Infrastructure


  • AWS & GCP

  • Docker

  • Kubernetes (preferred)

  • Terraform (nice to have)

  • CI/CD pipelines

  • Monitoring and logging

  • Security best practices

Leadership Experience

We're looking for someone who has:

  • Built and shipped production software at startup speed.

  • Led technical architecture decisions.

  • Worked closely with founders.

  • Mentored engineers or technical teams.

  • Balanced product velocity with engineering quality.

  • Strong communication skills with both technical and non-technical stakeholders.

Experience hiring and scaling engineering teams is highly desirable.

Nice to Have
  • Enterprise SaaS & PaaS experience.

  • Experience with document processing or intelligent automation.

  • OCR, search, or knowledge management platforms.

  • Financial Services,Legal, Insurance, Retail Industry experience.

  • Startup experience from Seed through Series A/B.

What Success Looks Like

Within your first 90 days, you'll:

  • Become the technical owner of the platform.

  • Understand the existing architecture and roadmap.

  • Ship meaningful product improvements.

  • Improve engineering velocity and release processes.

  • Help define the next-generation AI platform architecture.

Within your first year, you'll:

  • Scale the engineering organization.

  • Lead technical hiring.

  • Improve platform reliability and performance.

  • Deliver enterprise-grade AI capabilities.

  • Become a key technical leader for customers, investors, and strategic partners.




Benefits

Why Join Us?
  • Engineering leadership role.

  • Significant equity opportunity.

  • Build cutting-edge AI products from the ground up.

  • Work alongside experienced founders in AI, cloud, and enterprise technology.

  • Influence product, technology, and company strategy from day one.

  • Opportunity to shape the future of enterprise document intelligence.

If you're excited about building AI products, leading engineering, and creating category-defining technology, we'd love to hear from you.

More about this job

Responsibilities

Own the technical architecture and engineering roadmap, and lead development of AI-powered document intelligence products, scalable infrastructure, and reliable LLM, agentic, and RAG systems. Partner with product and customer teams, improve platform quality and delivery practices, and recruit, mentor, and scale the engineering organization.

Requirements

The role calls for a senior technical leader with experience shipping production software at startup speed, making architecture decisions, working with founders, and mentoring engineers. Relevant expertise includes AI/LLM systems, Python backend development, cloud infrastructure, distributed systems, and strong communication; experience hiring and scaling teams is highly desirable.

Skills

  • Technical Architecture
  • Engineering Leadership
  • Large Language Models
  • Agentic AI
  • Retrieval-Augmented Generation
  • Python
  • FastAPI
  • Backend Engineering
  • Distributed Systems
  • PostgreSQL
  • AWS
  • Google Cloud Platform
  • Docker
  • Kubernetes
  • Terraform
  • CI/CD

Benefits

  • Equity Opportunity

Visa sponsorship

Not detected in the job text

Categories

  • Technology
  • Software
  • Engineering
  • Management & Leadership
  • Data & Analytics

Keywords

  • Large Language Models
  • OpenAI
  • Anthropic
  • Gemini
  • Agentic AI
  • Retrieval-Augmented Generation
  • RAG
  • Vector Databases
  • Prompt Engineering
  • Evaluation Frameworks
  • AI Observability
  • LangGraph
  • LangChain
  • LlamaIndex
  • Python
  • FastAPI
  • REST APIs
  • Event-Driven Architectures
  • Distributed Systems
  • PostgreSQL
  • Redis
  • AWS
  • Google Cloud Platform
  • Docker
  • Kubernetes
  • Terraform
  • CI/CD
  • Enterprise SaaS
  • Document Processing

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