06 Sep
|
QuantumBlack, AI by McKinsey
|
Toronto
06 Sep
QuantumBlack, AI by McKinsey
Toronto
Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won’t find anywhere else.
Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development.
Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm’s diversity fuels creativity and helps us come up with the best solutions for our clients. On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family. You will be a technical owner, designing and leading the implementation of scalable data architectures for cutting-edge AI and agentic systems.
You will lead the development of robust data pipelines, manage secure and governed data environments, and mentor junior colleagues while collaborating with clients and cross-functional teams. You'll tackle impactful challenges and grow as a leader by architecting cutting-edge AI solutions across diverse industries. You will own and deliver technical workstreams, designing machine learning, agentic, and autonomous AI systems.
You'll lead the integration of machine learning, Generative AI capabilities and agentic frameworks into client solutions, designing MLOps/LLMOps-focused architectures for model management, observability, and automated retraining.
You will also spearhead the design of complex feature engineering workstreams, ensuring our data assets are not only robust but also optimized for the next generation of AI models. Your work will help solve some of the most complex and high-impact challenges facing clients across industries.
By partnering with QuantumBlack, AI by McKinsey and QuantumBlack Labs teams, you'll lead the creation of innovative enterprise-grade machine learning systems that accelerate AI adoption and solve critical business problems at speed and scale. You will be instrumental in shaping how we build and deploy high-impact AI systems, enabling clients to achieve meaningful, lasting impact through technical innovation. You'll be based in one of our North American offices as part of our global Data Engineering community.
You'll work in cross-functional Agile teams alongside Data Scientists, Machine Learning Engineers, and industry experts, leading the data engineering workstream to deliver AI solutions. Collaborating with clients from data owners to C-level executives, you'll help design impactful solutions that address complex business challenges and build client capabilities. You’ll develop deep expertise at the intersection of technology strategy and business value by addressing diverse architectural challenges.
Working with inspiring, multidisciplinary teams,
you’ll gain a holistic understanding of enterprise AI while collaborating with leading AI and data experts in the industry. Degree in Computer Science/Engineering, or equivalent experience ~5+ years of relevant professional experience in a data engineering role, with experience leading technical workstreams, mentoring junior engineers, and driving the adoption of software engineering best practices within a team ~ Expert-level proficiency in Python and SQL and the ability to work in polyglot environments (Scala, Java) when required by client enterprise systems ~ Strong experience building Agentic AI, Generative AI, Machine Learning, and Business Intelligence systems, including prompt design, retrieval‑augmented generation (RAG), embeddings, vector databases, context construction, and output handling in production workflows using modern frameworks (Spark, LangChain, Databricks, Dask, Airflow, Dagster, Kedro, etc.) ~ Ability to lead the implementation of AI features end to end, with sound judgment around model behavior, evaluation, reliability, guardrails, and the trade‑offs between quality, latency, and cost ~ Experience implementing robust data security and governance controls, including managing PII/PHI, authentication, and role‑based access control (RBAC) ~ Deep knowledge of MLOps/LLMOps including CI/CD for data workflows, automated agent evaluation (LangSmith, Opik, Langfuse), and infrastructure as code (Terraform) across cloud providers (AWS, Azure, GCP) ~ Exceptional time management and ability to own technical workstreams autonomously ~ Experience using coding agents (Cursor, Claude Code, Codex, etc.) Strong communication skills, both verbal and written, in English and local office language(s) #
📌 Senior Data Engineer I - QuantumBlack, AI by McKinsey (Toronto)
🏢 QuantumBlack, AI by McKinsey
📍 Toronto