GTM Engineer (Pacific Time)

Overview

Build and own the go-to-market engineering infrastructure for a fast-growing AI training data marketplace, helping a lean commercial team source, qualify and close opportunities at scale.

What you'll do

• Own the GTM tooling stack end to end, including selecting, configuring, integrating and maintaining the tools used by the commercial team.
• Build scalable sourcing systems, including scrapers and data enrichment pipelines, to identify relevant data providers and opportunities.
• Develop and maintain the data infrastructure behind GTM, connecting CRM, marketplace and product data into a reliable source of truth for pipeline, listings and revenue.
• Build internal tools to support provider research, listing quality checks, pipeline management and sales forecasting.
• Automate repetitive workflows across sourcing, qualification, lead routing and reporting.
• Identify operational bottlenecks with the founders and commercial team, prioritising automation projects with the highest impact.
• Explore and implement AI agents where they provide clear advantages over traditional automation.
• Make build-versus-buy decisions for GTM tooling, keeping the technical stack efficient, reliable and easy to maintain.

What you'll need

• 2+ years of professional software engineering experience.
• Strong programming skills in Python or TypeScript.
• Fluent SQL.
• Experience building internal tools, automations or integrations used by other teams in their day-to-day operations.
• Hands-on experience developing data pipelines and API integrations between different business systems.
• Strong problem-solving skills and the ability to translate business needs into practical technical solutions.
• Commercial awareness and an interest in revenue operations, with the ability to understand sales workflows and prioritise projects that directly support business growth.
• Clear written communication skills and the ability to take ownership in ambiguous, fast-moving environments.
• Fluent English.

Nice to have

• Experience in RevOps, growth engineering, sales engineering or forward-deployed engineering.
• Hands-on experience implementing LLMs or AI agents in production environments.
• Previous experience in an early-stage startup or as a founder.
• Familiarity with AI training data, including RL environments, evaluations and benchmarks.

Details

• Fully remote, aligned with US Pacific time zones (offices also available in San Francisco and Singapore).
• Full-time, start date ASAP.
• Working hours align with either Singapore or US Pacific business hours, depending on location.