GTM Engineer (Pacific Time)

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 United States, 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.