GTM Engineer (Pacific Time)

Jobgether; Canada; Remote; CAD 110,000 - 150,000; Full time

Benefits offered by this job

Fully remote from Canada

Pacific Time aligned

Autonomy and ownership

Collaborative leadership

Job summary

Jobgether, on behalf of a partner company, seeks a GTM Engineer in Canada to build and optimize the infrastructure powering commercial operations in a fast-growing AI and data environment.

You will treat go-to-market processes as an engineering challenge, developing scalable tools, data pipelines, integrations, and automations that accelerate growth, with autonomy and technical ownership.

Qualifications

• At least 2 years of professional software engineering experience.
• Strong programming in Python or TypeScript with fluent SQL knowledge.
• Hands-on experience building internal tools, workflow automations, and software integrations.
• Experience developing data pipelines and integrating APIs across systems.
• Strong analytical and problem-solving abilities; ability to translate business needs into technical solutions.
• Commercial awareness with focus on revenue operations and growth strategies.
• Excellent written communication and collaboration with technical and non-technical stakeholders.
• Autonomous, proactive work style with ownership in fast-moving environments.
• Fluent English, written and verbal, with ability to work across Pacific Time zones.

Responsibilities

• Take end-to-end ownership of the GTM technology stack; evaluate, configure, integrate, and maintain tools.
• Design and develop scalable sourcing systems and enrichment pipelines.
• Build data infrastructure unifying CRM, marketplace, and product data for pipeline tracking and revenue reporting.
• Develop internal tools to improve provider research, listing quality, sales pipeline, and forecasting.
• Automate repetitive GTM workflows from lead generation to reporting.
• Collaborate with founders and commercial stakeholders to translate business needs into tech solutions.
• Research and implement AI agents and intelligent automation where beneficial.
• Make build-versus-buy decisions to keep the stack efficient and scalable.
• Monitor and evolve systems as business requirements grow.

Skills

Python/TypeScript

SQL

Data pipelines

APIs

Automation

Analytical thinking

Communication

Ownership

English fluency

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a GTM Engineer (Pacific Time) based in Canada.

We are seeking a technically skilled GTM Engineer to build and optimize the infrastructure powering commercial operations within a fast-growing AI and data infrastructure environment. In this role, you will approach go-to-market operations as an engineering challenge, developing scalable tools, data pipelines, integrations, and automations that accelerate business growth. You will work closely with founders and commercial teams to identify operational bottlenecks and transform complex workflows into efficient, reliable systems. Your work will directly support lead generation, provider sourcing, pipeline management, and revenue operations. You will also explore AI-powered solutions and intelligent agents to improve productivity and automate repetitive processes. This is an engineering-first opportunity offering significant autonomy, technical ownership, and the chance to make a measurable impact in a dynamic, fast-paced environment.

Accountabilities:

• Take end-to-end ownership of the go-to-market technology stack, including evaluating, selecting, configuring, integrating, and maintaining tools used by commercial teams.
• Design and develop scalable sourcing systems, including web scrapers, data collection solutions, and enrichment pipelines to identify relevant data providers and commercial opportunities.
• Build and maintain the data infrastructure supporting commercial operations by integrating CRM, marketplace, and product data into reliable, centralized sources of information for pipeline tracking, listings, and revenue reporting.
• Develop internal applications and tools that improve provider research, listing quality assurance, sales pipeline management, and revenue forecasting.
• Automate repetitive commercial workflows across lead generation, sourcing, qualification, lead routing, and reporting to improve operational efficiency.
• Collaborate directly with founders and commercial stakeholders to identify operational challenges, prioritize high-impact automation initiatives, and translate business needs into technical solutions.
• Research, implement, and optimize AI agents and intelligent automation solutions where they offer clear advantages over traditional workflows.
• Make strategic build-versus-buy decisions to ensure the GTM technology stack remains efficient, scalable, reliable, and easy to maintain.
• Continuously monitor and improve existing systems, ensuring that technical infrastructure evolves alongside business requirements and commercial growth.

Requirements:

• At least 2 years of professional software engineering experience, ideally involving the development of business-critical tools, applications, or automation systems.
• Strong programming skills in Python or TypeScript, combined with fluent SQL knowledge and the ability to work with data-intensive applications.
• Hands-on experience building internal tools, workflow automations, and software integrations used by business or operational teams.
• Practical experience developing data pipelines and integrating APIs across multiple business systems and platforms.
• Strong analytical and problem-solving abilities, with the capacity to understand operational challenges and translate business requirements into practical, scalable technical solutions.
• Commercial awareness and a genuine interest in revenue operations, sales processes, and growth strategies, with the ability to prioritize engineering initiatives based on their business impact.
• Excellent written communication skills and the ability to collaborate effectively with technical and non-technical stakeholders.
• A proactive and autonomous working style, with the ability to take ownership, manage priorities, and deliver results in ambiguous and fast-moving environments.
• Fluent English communication skills, both written and verbal, and availability to work with teams operating on Pacific Time.

Nice-to-have qualifications:

• Previous experience in Revenue Operations (RevOps), growth engineering, sales engineering, or forward-deployed engineering.
• Practical experience implementing Large Language Models (LLMs) or AI agents in production environments.
• Previous experience working in an early-stage startup, high-growth technology company, or entrepreneurial environment, including founder experience.
• Familiarity with AI training data ecosystems, including reinforcement learning (RL) environments, model evaluations, and benchmarking.
• Experience working with CRM platforms, commercial data systems, and modern automation technologies.
• Strong curiosity about AI infrastructure and the practical application of emerging technologies to business operations.

Candidates who do not meet every listed requirement are still encouraged to apply. Strong engineering fundamentals, a sense of ownership, problem-solving abilities, and a willingness to learn are highly valued.

Benefits:

• Competitive compensation: Opportunity to join a high-growth AI and data infrastructure environment with compensation aligned with experience and expertise.
• Fully remote flexibility: Work remotely from Canada, with working hours aligned with the US Pacific time zone.
• High-impact responsibilities: Build the technical systems and infrastructure that directly support commercial operations and revenue growth.
• Direct founder collaboration: Work closely with founding leadership and commercial teams, contributing to strategic decisions and business priorities.
• Technical ownership: Take responsibility for the GTM technology stack and lead projects from identifying challenges through implementation and optimization.
• Modern AI technologies: Gain hands-on exposure to advanced AI tools, LLMs, intelligent agents, and automation technologies.
• Professional growth: Develop expertise at the intersection of software engineering, AI infrastructure, data systems, and commercial operations.
• Entrepreneurial environment: Join a fast-moving, innovative team where autonomy, experimentation, and practical problem-solving are encouraged.
• Flexible work arrangements: Benefit from a distributed working environment designed to support collaboration across international teams.