Principal Applied AI Developer, Foundation Models Infrastructure

Accountabilities: In this role, you will define and build the foundational infrastructure that enables scalable AI and ML development across the organization:

Define and drive technical strategy for foundation model and ML infrastructure across the platform ecosystem

Architect and build large-scale, resilient, secure, and cost-efficient systems supporting ML lifecycle stages (training, inference, deployment, evaluation, monitoring)

Develop and evolve developer-facing APIs, self-service tools, and workflows to accelerate ML development and deployment

Work hands-on with cloud-native technologies such as Kubernetes, AWS, Ray, and SageMaker to support distributed compute workloads

Translate ambiguous research, product, and business requirements into clear technical designs and executable engineering plans

Lead cross-team technical initiatives, aligning stakeholders and influencing architectural direction without formal authority

Establish and maintain platform standards for reliability, observability, SLAs/SLOs, versioning, governance, and production readiness

Improve system performance, scalability, cost efficiency, and operational reliability across ML workloads

Drive CI/CD, infrastructure-as-code, automated testing, and developer productivity improvements

Lead root-cause analysis of production issues and implement long-term platform-level solutions

Mentor senior engineers and elevate engineering excellence across teams

Collaborate with security, privacy, research, and product teams to ensure safe and responsible AI deployment practices

Requirements:

To succeed in this role, you bring deep expertise in large-scale systems, AI infrastructure, and technical leadership:

8+ years of software engineering experience, including strong exposure to distributed systems, cloud infrastructure, or ML platforms

Advanced experience designing and operating production-grade ML or AI infrastructure (training, inference, deployment, observability)

Strong hands-on expertise with Kubernetes and cloud-native architectures

Experience with distributed computing frameworks such as Ray, SageMaker, or equivalent ML infrastructure tools

Proven ability to lead complex, cross-functional technical initiatives and influence architecture decisions without direct authority

Strong background in CI/CD pipelines, infrastructure-as-code, automated testing, and production system operations

Experience translating ambiguous technical or business requirements into scalable system designs

Deep understanding of system design trade-offs across performance, reliability, cost, and scalability

Experience mentoring senior engineers and driving engineering best practices across teams

Excellent communication skills with the ability to engage both technical and non-technical stakeholders

Bonus: experience with AI-assisted development tools, agentic workflows, and modern AI engineering patterns

Bonus: familiarity with model governance, responsible AI practices, and ML lifecycle management at scale

Benefits:

Competitive annual base salary range: $153,000 – $224,400 CAD

Performance-based annual bonus and potential equity or stock grants

Comprehensive health, dental, and vision coverage

Hybrid or flexible work arrangements depending on location and team needs

Strong focus on innovation, learning, and professional development

Opportunity to work on large-scale foundation model infrastructure and cutting-edge AI systems

Inclusive, global engineering culture focused on collaboration and technical excellence

Access to mentorship, leadership development, and internal mobility opportunities

Exposure to high-impact projects shaping AI-driven products used worldwide

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether? 

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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