Clariti Cloud Inc.

Technical Product Manager, Applied AI

Canada (Remote) · Part-time

Sponsorship not specified$130k-$165kDetected 5 days ago

DevOpsPlatform EngineeringLLMsAgentic AILangGraphLeadershipMentoring

About the role

Your job is to scale them from one team's tooling into company infrastructure.
Prioritize and ship improvements to the agentic SDLC used by product development pods: agent specs, orchestration workflows, reusable prompts, and the eval harnesses that let us trust and improve agent output.

Own the Agentic SDLC framework roadmap.
Extend the Agentic SDLC framework into PS delivery. Partner with the PS leadership team to embed agentic workflows into active implementation projects, from discovery through build. Instrument the before and after so margin impact is measurable, not anecdotal.
Ship and maintain the connector layer (MCP integrations into our core systems), a curated skill and template library per function, and the onboarding paths that take an employee from zero to producing real work with AI.
Run the enablement flywheel. Own the AI fluency program end to end: assessments, coaching content, team-level reporting, and the feedback loop from usage data back into the harness roadmap. Enablement is a distribution problem, not a training problem
Own AI vendor and model strategy for internal use. Evaluate models, harnesses, and tools
Own governance for agent output. In govtech, agent-assisted work can end up in front of a planning commission. Define the audit trail, versioning, and approval standards for agent-produced artifacts, and make the safe path the easy path.
Proven ability to make powerful technology usable by non-technical people, including the judgment for when to build, buy, or simply document.

5+ years in technical product management, platform engineering, solutions engineering, or applied AI roles, with at least 1 to 2 years shipping LLM or agentic systems into production or into daily internal use.
you have personally built with agent frameworks (Claude Code, LangGraph, or equivalents), MCP or comparable tool protocols, and eval-driven iteration.
You can read and write an agent spec, not just commission one.
Hands-on fluency with the current agentic stack: you have personally built with agent frameworks (Claude Code, LangGraph, or equivalents), MCP or comparable tool protocols, and eval-driven iteration.

We invest in and empower our team members with competitive compensation packages, well deserved time off and benefits to keep you and your family healthy! *

This listing is sourced directly from Clariti Cloud Inc.'s careers page and normalized into a canonical job model.