AI Data scientist + Data Engineer

Company Description

Spruce InfoTech, a leading IT firm, offers innovative and cost-effective solutions to help clients manage and transform their businesses. Our services are designed to guide companies of all sizes, from small businesses to Fortune 500 organizations, in maximizing their IT investment while reducing technology costs. Our team of experts has extensive technical knowledge in enterprise solutions, which helps organizations transform these solutions into a strategic asset that can drive new revenue and improve business operations.

Website

http://www.spruceinfotech.com

Job Description

Data Engineer and Data scientist

Hybrid role – 2 to 4 days in Toronto downtown / week.

Combination role of AI data scientist + Data Engineer – Must have

JD below – a mix of Data engineer and data scientist.

What will you do?

• Design, build, and scale GenAI-driven systems that power research digitization, banking workflows, global markets, and monetization pipelines
• Develop and productionize APIs and intelligent services backed by large language models (LLMs) and semantic search
• Build and manage Kubernetes-deployed MCP servers using FastAPI, supporting dynamic routing, prompt orchestration, and multi-source data access
• Implement high-performance Spark workloads on Databricks and Delta Lake to support structured and unstructured data flows
• Collaborate with platform teams, AI scientists, and business stakeholders to deliver context-aware, AI-integrated tools
• Drive CI/CD automation, testing, and infrastructure-as-code for scalable and secure releases

Must Have

• Strong backend development skills in Python, FastAPI, and async programming
• Solid hands-on experience with Kubernetes, Docker, and API deployment at scale
• Deep understanding of Databricks, Delta Lake, PySpark, and distributed data workflows
• Proven experience building or integrating with LLM-based applications, including prompt routing or semantic matching
• Excellent debugging, profiling, and optimization skills in high-throughput environments
• Comfort working with cloud platforms, especially Azure

Nice to Have

• Familiarity with model orchestration frameworks (LangChain, LlamaIndex, or similar)
• Experience designing or contributing to MCP-style architectures (multi-modal, intent-aware, tool-executing systems)
• Working knowledge of MLflow, Airflow, or Snowflake
• Exposure to alternative data sources (web, satellite, social, geospatial) and their AI use cases
• Understanding of enterprise CI/CD, secrets management, and secure API gateways