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Posted 13 days ago

AVP, Lead Software AI Engineer

@ Encore Technical Solutions Inc.

Toronto, Ontario

Full-time
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SIGNALS

Requirements summary:

  • Required Qualifications
  • Approximately ten years of professional software development experience , including substantial experience delivering AI or machine learning solutions in production environments.
  • Advanced proficiency in Python and TypeScript , with experience across both backend and frontend development.
  • Hands-on experience designing and implementing retrieval-based LLM applications .
  • Experience integrating commercial LLM APIs into user-facing applications.
  • Proven experience operating containerized applications on Kubernetes within automated deployment pipelines.
Source and dates

Source type not verified · apify-linkedin

Employer posting date
2026-10-28
First seen by our source
2026-11-10
Source record updated
2026-11-10

These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.

Encore Technical Solutions Inc.

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Job description

AVP - Senior Engineering Lead, AI Software Engineering

Location: Toronto, ON | Work arrangement: [Hybrid] | Employment type: Full-time, Permanent

About the Opportunity

Our client, a large and well-established enterprise organization, is looking for a Senior Engineering Lead to oversee the continued development of its internal generative AI platform. The platform is already in production and supports a large employee user base.

The successful candidate will be accountable for the platform’s technical direction and quality. The role is heavily hands-on: alongside providing technical leadership to a small development team, the incumbent will spend most of their time on development work.

Key Responsibilities

Technical Delivery

  • Design, develop and maintain production services and user interfaces in Python and TypeScript.
  • Improve the platform’s retrieval-augmented generation capabilities, including document segmentation, semantic and keyword search, result ranking and response streaming.
  • Enhance document ingestion processes for a range of file formats, including scanned content requiring optical character recognition.
  • Evaluate large language model and embedding services for accuracy, performance and cost, and recommend improvements based on the findings.
  • Manage containerized deployments, automated build and release pipelines, and the promotion of releases through testing environments to production.
  • Establish monitoring, alerting and service-level objectives, and lead incident resolution and post-incident reviews.
  • Assess emerging AI techniques and bring suitable ones into production.

Leadership and Stakeholder Engagement

  • Provide technical guidance to a small team of engineers through design reviews, code reviews and mentorship.
  • Work with product owners and business partners to define AI solutions with measurable outcomes.
  • Communicate technical direction, risks and tradeoffs to senior leadership in clear, non-technical terms.

Required Qualifications

  • Approximately ten years of professional software development experience, including substantial experience delivering AI or machine learning solutions in production environments.
  • Advanced proficiency in Python and TypeScript, with experience across both backend and frontend development.
  • Hands-on experience designing and implementing retrieval-based LLM applications.
  • Experience integrating commercial LLM APIs into user-facing applications.
  • Proven experience operating containerized applications on Kubernetes within automated deployment pipelines.
  • Strong working knowledge of a major public cloud platform.
  • A demonstrated record of delivering and supporting production systems.
  • Excellent written and verbal communication skills, including experience presenting to senior stakeholders.

Preferred Qualifications

  • Experience with document processing or OCR solutions at scale.
  • Familiarity with agent-based AI architectures and tool-calling workflows.
  • Regular use of AI-assisted development tools.
  • Experience in a regulated industry.
  • Contributions to open-source projects.

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