Staff AI Engineer

This is a fully remote position, open to applicants in Canada.

📋 Description

• Actively contribute by writing and deploying production AI code on a daily basis.

• Lead the retrieval of customer context utilizing semantic retrieval, indexing, and knowledge graph methodologies.

• Facilitate agents in resolving customer inquiries and retrieving their complete context within a single request.

• Develop inference and signal layers over the Iceberg-based lakehouse architecture.

• Record scored inferences back to the data platform and make signals available through contracts for other teams.

• Translate signals such as churn risk, usage discrepancies, and expansion opportunities into actionable workflows.

• Choose the suitable large models, finely-tuned smaller models, or deterministic code for each specific workload.

• Oversee inference costs effectively.

• Take ownership of evaluation and observability for AI systems.

• Create patterns for other teams and collaborate with engineering and business leaders to achieve company objectives.

• Work in conjunction with observability, core data platforms, and insights and intelligence teams alongside product and platform teams.

• Design, construct, and deploy production systems while maintaining a rapid iteration cycle.

⛳️ Requirements

• More than 8 years of software engineering experience, including at least 3 years of delivering AI or ML systems to production.

• Strong programming fundamentals with deep expertise in at least one language relevant for AI and data work; Python being the primary language for ML and insights.

• Proficiency in handling data at scale, including advanced SQL, transformation layers such as dbt, and distributed query engines over lakehouse or warehouse storage.

• Experience in assessing query costs and implementing partitioning strategies.

• Expertise in production retrieval and context engineering, involving embeddings, vector search, hybrid or graph retrieval, and evaluating retrieval effectiveness.

• Familiarity with agentic systems and robust workflows in production, including tool invocation, state and memory management, and human-in-the-loop approaches.

• Competence in evaluation and observability of AI systems, which includes tracing, prompt and version management, and dataset-driven testing.

• Experience in cloud deployment, preferably with AWS, focusing on containerized services and ownership of inference costs.

• Bachelor’s degree in Computer Science or equivalent practical experience.

• Background in shared data or ML capabilities used by other teams.

• Experience with smaller and finely-tuned models, including distilling task-specific models.

• Fluency in observability data, including OpenTelemetry and high-volume logs, metrics, and traces.

• Knowledge of data governance, encompassing access control, lineage, and data residency.

• Experience in enterprise SaaS or CMS, with familiarity with Acquia's Drupal-based DXP.

• Acquainted with AI-assisted coding tools such as Claude, Cursor, or Copilot, and MCP or equivalent technologies.

• Excellent communication skills for discussing AI system designs with engineers and C-suite stakeholders.

• Proven record as a senior individual contributor, including mentoring through technical work.

• Demonstrated fluency in AI, an orchestration mindset, radical adaptability, a builder mentality, and intellectual humility.

🏝️ Benefits

• Competitive healthcare coverage.

• Wellness programs.

• Flexible time off as needed.

• Parental leave.

• Recognition programs.

• Inclusive, transparent, efficient, and educational interview process.

• Opportunities for career growth and learning from a global team.