Forward Deployed Engineer (Data, ML & AI)
$160,000–$180,000 year
RemoteCanada
Job Summary
Deploy directly into customer environments to assess legacy data estates and build scalable modern data platforms. Own end-to-end delivery from data discovery and schema design to pipeline deployment and model integration using Spec-Driven Development workflows. Architect and deploy GenAI workflows, RAG pipelines, and autonomous AI agents while establishing robust evaluation frameworks for accuracy and latency. Build, maintain, and orchestrate ML training and inference pipelines using tools like MLflow, Kubeflow, and Airflow, ensuring continuous integration and deployment for all data and model workflows. This role requires 10+ years of experience as a Principal Data Engineer or Lead ML Engineer with deep expertise in distributed computing, cloud-native services, and polyglot data engineering. Compensation ranges from 160K to 180K CAD annually, with a competitive benefits package including RRSP matching, health premiums, and flexible remote work arrangements.
Required Qualifications
- 10+ Years of Experience
- Proven track record as a Principal Data Engineer, Lead ML Engineer, or Enterprise Data Architect building and scaling distributed data and ML platforms
- Strong executive presence and communication skills to interface directly with technical teams and business stakeholders under pressure
- Mastery of distributed computing (AWS Glue, Apache Spark, Databricks)
- Experience with modern data warehouses (Redshift, Snowflake)
- Experience with modeling tools (dbt)
- Experience with data orchestration (Airflow)
- Hands-on experience fine-tuning, evaluating, and deploying LLMs
- Experience with embedding models
- Experience with vector stores
- Advanced proficiency in Python
- Advanced proficiency in complex SQL
- Fluency in at least two other languages used in modern backend/data systems (e.g., Scala, Go, Rust, TypeScript)
- Demonstrated skill in using natural language and structured specs to guide AI tools (Claude Code, Cursor, Copilot) in generating data pipelines, schemas, and API adapters
- Hands-on experience with cloud-native data services on AWS or Azure
- Experience with containerization (Docker, Kubernetes)
- Experience with Infrastructure as Code (Terraform)
- Comfort with occasional travel to customer sites as needed
Desired Qualifications
- Prior experience in a Forward Deployed Engineer, Data Architect, or technical consulting/professional services role
- Experience migrating legacy, on-premise data warehouses or legacy Hadoop estates to modern cloud lakehouses
- Deep understanding of data governance, security compliance (HIPAA, SOC2, GDPR), and privacy-preserving machine learning
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