Director of Technical Support Engineering in Haciendas del Canada, Nuevo León at Jobgether

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Director of Technical Support Engineering based in Canada.

As Director of Technical Support Engineering, you will lead the transformation and development of a global technical support organization for an innovative, AI-driven enterprise technology platform. You will own the entire customer support experience, ensuring technical issues are investigated, resolved, and continuously transformed into opportunities for improvement. Combining hands-on technical expertise with strategic leadership, you will build and develop high-performing distributed engineering teams while introducing AI-powered support systems and intelligent automation. You will establish scalable processes, strengthen collaboration with Product and Engineering, and drive measurable improvements in customer satisfaction, operational efficiency, and service reliability. This is an exciting opportunity to shape a modern, AI-native support function in a remote-first, fast-growing technology environment.

• Build and lead the Technical Support Engineering function: Recruit, develop, and manage a high-performing team of technical support engineers, establishing strong technical standards across SQL, APIs, debugging, and cloud data systems while remaining directly involved in complex customer investigations.

• Develop a distributed support organization: Expand and manage geographically distributed teams, initially focusing on India, and establish sustainable staffing models, coverage strategies, and resource allocation based on workload, industry benchmarks, and operational economics.

• Build an AI-native support organization: Design and implement AI-assisted workflows for issue intake, triage, investigation, and diagnostics, leveraging approved knowledge bases, logs, telemetry, and authorized customer information to improve resolution speed and consistency.

• Ensure responsible AI implementation: Evaluate AI-powered support solutions against real customer cases, establish privacy controls, permissions, human approval processes, and escalation procedures, and progressively expand automation based on measurable improvements in quality and productivity.

• Own the end-to-end customer support experience: Oversee the entire support lifecycle, from initial intake and prioritization through technical investigation, escalation, resolution, and customer communication, ensuring clear ownership and seamless handoffs between support levels and other teams.

• Manage service levels and incident response: Establish and maintain service standards, including reliable 24/7 critical incident coverage, structured escalation paths, sustainable on-call rotations, backup coverage, and effective recovery practices following overnight incidents.

• Strengthen knowledge management and automation: Modernize customer documentation, internal knowledge bases, and technical runbooks, managing version-controlled resources through GitHub and establishing clear review, validation, and publishing standards.

• Improve technical diagnostics and self-service: Turn recurring investigations into reusable documentation, diagnostic scripts, and automated tools that improve visibility into customer workloads, integrations, and infrastructure while reducing repetitive support requests.

• Partner with Product and Engineering: Establish shared escalation processes, improve incident ownership, support root cause analysis, and drive permanent product and infrastructure improvements while minimizing unnecessary engineering interruptions.

• Drive operational performance: Monitor response times, resolution rates, SLA attainment, customer outcomes, and team workload, using support trends and operational insights to inform product reliability, observability, and customer experience improvements.

• Proven experience building, scaling, or transforming technical support engineering organizations, including recruiting, managing, and coaching distributed technical teams.

• Strong hands-on technical troubleshooting experience across SQL, APIs, authentication, data schemas, synchronization processes, and data exports.

• Demonstrated ability to develop diagnostic scripts, internal tools, and automation that improve investigation efficiency and support outcomes.

• Experience designing, implementing, and evaluating AI-enabled support systems, including grounded AI responses, permission management, failure analysis, risk controls, and human escalation workflows.

• Experience developing structured, version-controlled technical documentation, knowledge bases, and operational runbooks with clear review and publishing processes.

• Strong customer-focused judgment and the ability to prioritize complex issues according to business impact, severity, and contractual commitments, even when the underlying cause is unclear.

• Excellent communication skills, including the ability to manage customer expectations, communicate uncertainty transparently, and coordinate effectively with technical and non-technical stakeholders.

• Experience with capacity planning, workforce management, operational benchmarking, and support economics, with the ability to build sustainable and scalable support models.

• Strong leadership and coaching capabilities, with a hands-on, accountable approach to problem-solving and continuous improvement.

• Ability to collaborate closely with Engineering, Product, Services, Customer Architects, and other customer-facing teams to improve the overall customer experience.

Nice to have:

• Experience supporting enterprise data platforms, cloud data warehouses, or marketing technology solutions, including audience activation and destination integrations.

• Experience scaling technical support teams based in India.

• Familiarity with Knowledge-Centered Service (KCS) methodologies.

• Experience safely expanding internal AI assistants into customer-facing support operations.

• Previous experience building support functions for complex, data-intensive enterprise software products.

• Competitive annual base salary:

  • Canada: CAD $240,000–$250,000.

  • United States: USD $170,000–$180,000.

• Equity compensation and additional variable compensation opportunities.

• Fully remote, flexible-first working environment with teams distributed across North America and beyond.

• Flexible, goal-oriented working arrangements.

• Flexible paid time off.

• Monthly company-wide Recharge Days to support rest and well-being.

• Annual home office stipend to support a productive remote workspace.

• Comprehensive health coverage, including:

  • 100% employer-paid individual medical coverage, with strong dependent contributions.

  • Employer-paid health, dental, vision, life, and disability insurance for Canadian employees.

• Retirement savings program through an RRSP in Canada or 401(k) in the United States, with generous company matching.

• Annual professional development stipend.

• Quarterly hackathons offering opportunities to explore innovative ideas and personal projects.

• Opportunity to work directly with an experienced executive team and collaborate with talented professionals across multiple disciplines.

• A learning-oriented culture that encourages experimentation, ownership, innovation, and continuous professional growth.