Technical Product Manager

Canada·TorontoFull-Timemid

Product ManagementProduct ManagerTechnical Product Manager

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Quick Summary

Overview

About ShyftLabs At ShyftLabs, we live and breathe data. Since 2020, we’ve been helping Fortune 500 companies unlock growth with cutting-edge digital solutions that transform industries and create measurable business impact.

Technical Tools

ab-testingagileci-cddatabase-designdistributed-systemsmachine-learningstakeholder-management

About ShyftLabs

At ShyftLabs, we live and breathe data. Since 2020, we’ve been helping Fortune 500 companies unlock growth with cutting-edge digital solutions that transform industries and create measurable business impact. We’re growing fast and we’re looking for passionate problem-solvers who are ready to turn big ideas into real outcomes.

The Opportunity

We’re a fast-growing startup redefining how automation, AI, and modern data infrastructure power business decisions. We’re looking for a seasoned Technical Product Manager (TPM) to lead the full lifecycle of complex AI and data initiatives, with a strong focus on data management, agentic system orchestration, and evaluation frameworks.

In this role, you’ll define technical strategy across data platforms and AI products, drive execution of agent-based systems end-to-end, and ensure scalable, governed, and measurable delivery. You will operate at the intersection of data architecture, AI orchestration, and product strategy, partnering closely with engineering to build systems that are robust, observable, and continuously improving.

Own and drive the end-to-end lifecycle of AI- and data-intensive technical initiatives across multiple products.

Define and evolve data management strategy, including data modeling standards, pipeline requirements, governance, lineage, and quality frameworks.

Lead product strategy for agentic systems, including orchestration layers, tool usage patterns, memory/context management, guardrails, and fallback strategies.

Establish and operationalize evaluation frameworks for AI products (LLM evals, benchmarking, human-in-the-loop review, automated scoring, drift monitoring).

Partner with engineering to design scalable architectures that support data ingestion, transformation, context retrieval, and multi-agent coordination.

Translate business objectives into clear technical specifications spanning APIs, data contracts, orchestration logic, and observability requirements.

Define metrics for success across system performance, data quality, model reliability, latency, cost optimization, and user outcomes.

Identify and mitigate risks across model behavior, data integrity, security, and compliance.

Oversee validation processes for AI systems, including regression testing, prompt versioning, evaluation harnesses, and continuous improvement loops.

Act as a bridge between product, data engineering, ML engineering, and platform teams to ensure technical alignment and delivery excellence.

Communicate roadmap progress, architectural trade-offs, and performance insights to executive stakeholders with clarity and rigor.

Foster a culture of accountability, structured experimentation, and high technical standards across teams.

Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related technical field.

2–5 years of experience in technical product management, preferably in AI, ML, or data platform environments.

Strong understanding of data architecture and data management principles, including data modeling, governance, lineage, quality monitoring, and cloud data platforms.

Demonstrated experience working on AI-powered or agent-based products, including orchestration patterns and evaluation methodologies.

Familiarity with LLM concepts such as context windows, retrieval augmentation (RAG), prompt orchestration, tool calling, memory management, and guardrails.

Experience defining and operationalizing evaluation frameworks (offline/online testing, experimentation, quality metrics, performance benchmarking).

Deep understanding of cloud computing platforms, distributed systems, APIs, and integration patterns.

Hands-on exposure to Agile methodologies, DevOps practices, and CI/CD pipelines.

Strong analytical thinking, structured problem-solving, and data-driven decision-making skills.

Excellent communication and stakeholder management abilities, including executive-level reporting.

$130,000 - $160,000 (CAD)