VP Of Engineering
TrackTik
Software Engineering
Montreal, QC, Canada
Posted on Jan 5, 2026
At Trackforce, we’re transforming how physical security operations are managed across the globe. As the world’s leading SaaS platform for physical security workforce management, we empower security companies and organizations with a streamlined solution to manage their guard forces. Our technology helps teams respond faster, operate more efficiently, and drive down costs - all while staying focused on what matters most: safety and protection.
We support over 4,600 clients in more than 50 countries and are proud of our growing team of 300+ professionals. With global offices that include headquarters in Dallas, Texas and Centers of Excellence in Montreal, Quebec and Wroclaw, Poland, we collaborate across borders and time zones in a dynamic hybrid work environment that values connection, flexibility, and impact.
Role Summary
TrackTik is scaling its end-to-end workforce management platform used by security service organizations worldwide. We’re now looking for a VP of Engineering who can drive predictable delivery, modernize the architecture, strengthen engineering culture, and now—critically—lead our evolution into an AI-augmented product and AI-driven engineering organization.
You will partner tightly with the CTO to translate strategy into an engineering operating model that ships, scales, and stays reliable. Expect to lead through ambiguity, remove blockers with urgency, and turn a historically reactive environment into a high-performance, outcome-driven engineering organization.
Key Responsibilities
- Technology & Architecture Leadership
- Define and enforce the technical vision and architectural roadmap across multiple product functions (mobile, scheduling, time/attendance, reporting, integrations).
- Modernize legacy components while ensuring continuity and stability for enterprise customers.
- Champion secure-by-design and performant systems; drive a shift to observability-first engineering.
- Establish a technical foundation for AI services, vector stores, data pipelines, and scalable inference infrastructure.
- Implement guardrails for responsible AI use: data privacy, model validation, auditability, and customer-facing transparency.
- Delivery & Execution
- Own predictable delivery—quarterly planning, execution, quality, and release cadence.
- Build and scale engineering processes that balance speed with stability (LEAN, CI/CD, trunk-based development, etc.).
- Reduce technical debt with a clear, measurable, investment plan.
- Drive end-to-end delivery for AI features—from experimentation to product ionization—with clear KPIs and success metrics.
- Introduce pipelines for model testing, deployment, monitoring, and lifecycle management.
- Team Leadership & Organizational Design
- Lead and grow a multi-disciplinary engineering organization (backend, frontend, mobile, QA).
- Develop high-performing engineering leaders; set clear expectations and enforce accountability.
- Strengthen engineering culture based on ownership, transparency, and continuous improvement.
- Build internal AI capabilities by hiring AI engineers, integrating AI specialists into squads, and upskilling existing engineers through training and enablement.
- Partner with Product to mature AI literacy across the entire organization.
- Cross-Functional Collaboration
- Partner with Product Management on roadmap definition, scoping, estimates, and tradeoff decisions.
- Collaborate with Customer Success, Support, and Sales Engineering to close feedback loops and accelerate quality improvements.
- Represent engineering at the senior leadership level and to customers when needed.
- Collaborate with Product to identify where AI enhances workflows: incident prediction, scheduling optimization, reporting automation, guard activity intelligence, anomaly detection, and operational forecasting.
- Work directly with customers on AI adoption, ensuring enterprise readiness and alignment with compliance requirements.
- Operational Excellence
- Own uptime, performance, incident response, security posture, and SLO/SLI maturity.
- Drive metrics-driven engineering (DORA, defect rates, cycle time, operational KPIs).
- Build out robust on-call, escalation, and root-cause analysis processes.
- Use AI to optimize internal operations—e.g., automated triage, anomaly detection in logs, predictive scaling, and support-ticket classification.
- Ensure AI features meet enterprise reliability and audit expectations, including drift detection and model performance monitoring.
- Strategic Impact
- Translate company strategy into engineering priorities and resourcing plans.
- Forecast hiring, budgets, vendor needs, and long-term technical investments.
- Act as a key voice in corporate decision-making as the business scales into new markets and product capabilities.
Required and Preferred Experience
- Required Experience
- 10+ years in software engineering with 5+ in senior engineering leadership roles (Director/VP).
- Proven success leading engineering teams in a SaaS company with large enterprise clients.
- Demonstrated ability transforming engineering orgs and modernizing legacy systems without destabilizing critical operations.
- Strong track record managing organizations of 30–80+ engineers across multiple squads.
- Experience with cloud-native systems (AWS preferred), distributed architecture, and security-sensitive environments.
- Excellent communicator who can handle exec-level debates, customer escalations, and difficult prioritization discussions.
- Experience shipping AI-powered features.
- Familiarity with modern AI tooling: LLMs, vector databases, embeddings, ML Ops, and cloud-based AI infrastructures.
- Preferred Experience
- Background in workforce management, physical security tech, compliance-heavy SaaS, or operationally intensive B2B & B2C products.
- Experience integrating with large enterprise ecosystems (HRIS, payroll, scheduling, IoT/guard-tour systems).
- Prior success supporting a platform undergoing international scale or multi-product expansion.
- Experience using AI to optimize workforce operations, predictive analytics, or scheduling automation.
- Experience evaluating LLM vendors, fine-tuned models, and domain-specific AI approaches.
Success Looks Like
- Predictable, high-quality releases—no surprises, no thrash.
- Engineering leaders who own outcomes and deliver autonomously.
- Architecture that scales and doesn’t slow down feature velocity.
- A culture where technical decisions are intentional, measurable, and aligned with the business.
- Material reduction in outages, defects, and firefighting.
- A roadmap that engineering can deliver without heroic effort.
Working at TrackForce
We're passionate about building a workplace where innovation, growth, and purpose come together. Whether you're in the office or working from home part of the week, you'll be part of a collaborative team that’s committed to delivering real value to our customers - and having fun while doing it.
At Trackforce, we live by our core values:
· Foster Curiosity
· Lead with Empathy
· Take Ownership and Be Accountable
· Empower Diversity
· Be True and Act with Integrity
#LI-Hybrid
At Trackforce, we are committed to providing a workplace that is inclusive, respectful, and free from discrimination. We do not tolerate discrimination or harassment of any kind, whether based on race, color, nationality, ethnic or social origin, religion or belief, sex, gender identity or expression, sexual orientation, age, disability, marital or family status, or any other protected status under applicable local laws.
We believe that a diverse and inclusive team fosters innovation, collaboration, and stronger business outcomes. Employment decisions are made based on qualifications, merit, and business needs. We are proud to be an equal opportunity employer and to comply with the employment laws of the countries where we operate.
