Jobs at Clariti Cloud Inc.

Conduct high-volume inbound and outbound prospecting to local government agencies across North America. Build multichannel sequences, research prospects using AI tools, identify buying stakeholders, qualify leads, maintain Salesforce pipeline data, coordinate handoffs to sales executives, and share market intelligence. The role requires cold calling, consultative communication, data-driven outreach optimization, and collaboration with Marketing and Sales. This is a full-time, 12-month contract with potential growth into full-cycle sales or customer success.

Leads enterprise SaaS implementation engagements from planning through delivery, managing project governance, schedules, budgets, milestones, risks, quality, customer expectations, and executive communications. Directs Professional Services teams and coordinates customers, system integrators, and internal stakeholders. The role also supports practice development, organizational change, process improvement, escalation management, and successful delivery of complex, multi-year transformation projects.

Build and ship production web applications for government permitting, licensing, plan review, and inspection workflows. Direct and review AI coding agents, write specifications and acceptance criteria, and own correctness, performance, security, testing, and user experience. Collaborate within a senior product engineering pod, improve agentic development workflows, and learn municipal software domains. Success requires independently delivering reliable features and improving team engineering practices.

Leads software implementation projects by assessing business requirements, designing and configuring Clariti and Salesforce solutions, documenting specifications, managing customer and system integrator stakeholders, and presenting solution deliverables. Supports Agile delivery, data migration, testing, and AI-assisted implementation workflows while ensuring solutions align with best practices and project scope.

Owns QA strategy and automation for an agentic development workflow. Responsibilities include designing Playwright and TypeScript end-to-end and API tests, reviewing AI-generated tests and code, building CI/CD quality gates, conducting risk-based exploratory testing, tracking quality metrics, triaging failures, and improving test architecture, data, environments, and team testing practices.

Lead enterprise Clariti implementations from discovery through delivery, serving as the functional and solution design authority. Facilitate workshops, translate requirements into scalable configurations, manage scope and risks, guide Salesforce and Clariti solutions, oversee SI partners, approve user stories, and mentor consultants. Apply AI to requirements documentation, user-story generation, and testing while driving customer outcomes and implementation efficiency.

Lead applied AI initiatives from problem scoping and experimentation through production deployment. Build and fine-tune LLM, agentic AI, computer vision, NLP, and multimodal systems; establish MLOps workflows; evaluate model performance; and make trade-offs across accuracy, interpretability, latency, and cost. Partner with product and engineering teams, communicate technical decisions to stakeholders, and contribute to AI research rigor and technical direction.

Design and scale ML infrastructure, pipelines, deployment systems, and agentic AI workflows. Build cloud-based training and serving infrastructure, implement CI/CD, monitor model performance and drift, optimize costs, and ensure reproducibility and reliability. Collaborate with AI researchers and engineers to productionize models, automate retraining, manage data pipelines, and establish MLOps best practices.

Own the technical delivery of government customer implementations, including legacy data extraction, transformation, migration, integrations, configuration, staging, and production cutovers. Partner with customers, consultants, and SaaS engineers on workflows, SSO, GIS, payments, and security reviews. Write production code, develop reusable tooling, and establish the Forward Deployed Engineer playbook. Use AI coding agents to accelerate delivery while ensuring scalable, auditable, data-integrity-focused implementations.