Manager, Software Engineering & AI
Role Overview
Leads a multidisciplinary team of AI engineers, frontend developers, and backend developers building internal AI agents, intelligent workflows, and enterprise applications.
Works with Python, LangGraph, Langfuse, MCP, Google Cloud, React, and JavaScript; guides architecture, delivery, talent development, and cross-functional collaboration.
Key Skills for This Role
Full Job Posting
Role overview
Leads a multidisciplinary team of AI engineers, frontend developers, and backend developers building internal AI agents, intelligent workflows, and enterprise applications.
Works with Python, LangGraph, Langfuse, MCP, Google Cloud, React, and JavaScript; guides architecture, delivery, talent development, and cross-functional collaboration.
Workplace
- Hybrid work model with four days in the office.
Responsibilities
- Lead hiring, onboarding, coaching, performance management, and career development for the engineering team.
- Identify AI and workflow-automation opportunities with business teams and product partners; define priorities, roadmaps, and delivery plans.
- Guide architecture and delivery of AI applications, agents, and workflows; oversee frontend, backend, and integrations.
- Establish standards for design, code quality, testing, reviews, CI/CD, and production readiness.
- Ensure secure, reliable, scalable, observable, and maintainable enterprise solutions.
- Manage risks, dependencies, delivery, and production health; support incidents and continuous improvement.
- Coordinate with architecture, security, data, infrastructure, and platform teams and communicate progress and risks.
Required qualifications
- 5+ years of professional software engineering experience and 2+ years leading or managing engineering teams.
- Experience hiring, mentoring, and developing engineers across AI, frontend, and backend disciplines.
- Knowledge of architecture, system design, APIs, distributed applications, and production enterprise applications.
- Working knowledge of LLM applications, AI agents, RAG, prompt engineering, and tool calling.
- React, JavaScript, Python, RESTful APIs, Google Cloud or another major cloud, testing, Git, CI/CD, observability, and production support experience.
- Understanding of privacy, application security, AI safety, and responsible AI; Agile and cross-functional delivery experience.
Assets
- Assets include Vertex AI, Gemini, BigQuery, vector databases, embeddings, semantic search, Docker, enterprise workflow automation, highly available applications, retail or e-commerce, JIRA, and Confluence.
Compensation
- Hiring range is CAD 120,000–154,000 per year; pay may vary by experience, knowledge, and location.
Screening
- The employer states that candidates aged 18 or older must complete a criminal background check.
- The company uses AI to screen, assess, or select applicants.
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