AI Engineering Manager

This is a fully remote position, open to applicants in Canada, +2 more states.

📋 Description

• Take ownership of product architecture, incorporating AI/LLM-integrated components.

• Develop systems that are scalable, secure, and maintainable.

• Lead strategic decisions regarding:

• o LLM integration (such as OpenAI, Azure OpenAI, etc.).

• o RAG architectures and vector databases.

• o AI orchestration frameworks (including LangChain, Semantic Kernel, LlamaIndex).

• Ensure system reliability, observability, and cost-effectiveness.

• Establish governance for AI and promote safe usage practices.

• Implement contemporary AI methodologies, which include:

• o Retrieval-Augmented Generation (RAG).

• o Prompt engineering and assessment.

• o Validation and guardrails for AI outputs.

• o Human-in-the-loop workflows.

• o Monitoring models and evaluating performance.

• Promote experimentation, A/B testing, and decision-making based on telemetry.

• Guide and mentor developers and QA engineers.

• Enhance AI literacy within the team.

• Establish coding and review standards tailored for AI.

• Balance the aspects of speed, quality, and architectural soundness.

• Manage reliable and high-quality releases.

• Ensure AI features are quantifiable, validated, and ready for production.

• Serve as a technical escalation point.

• Foster cross-team alignment with Product, Data, and DevOps departments.

• Utilize AI-assisted development tools to boost productivity.

• Optimize the trade-offs between AI costs and performance.

• Incorporate automation into testing and CI/CD pipelines.

⛳️ Requirements

• Over 7 years of software engineering experience, with a minimum of 2 years in a technical leadership role.

• Practical experience in building and deploying AI-powered systems.

• In-depth knowledge of:

• - LLM integration and prompt design.

• - RAG architectures and vector search technologies.

• - AI orchestration frameworks.

• - Cloud platforms (such as Azure, AWS, or GCP).

• Experience in designing scalable distributed systems.

• Familiarity with regulated industries.

• Understanding of AI governance and compliance.

• Knowledge of model lifecycle management and monitoring tools.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Flexible work hours and remote work options.

• Opportunities for professional growth and development.

• Comprehensive health and wellness benefits.

• Collaborative and innovative work environment.