Publié il y a 13 jours
AVP, Lead Software AI Engineer
@ Encore Technical Solutions Inc.
Toronto, Ontario
Résumé des exigences :
- 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 et dates
Type de source non vérifié · apify-linkedin
- Date publiée par l’employeur
- 2026-10-28
- Première détection par notre source
- 2026-11-10
- Mise à jour du dossier source
- 2026-11-10
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
Encore Technical Solutions Inc.
| Champ | Valeur |
|---|---|
| Offres sur Jobsy | 2 |
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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