As a Senior GTM Engineer, you’re a hands-on, full-stack builder embedded in an Ops team (Customer Success, Sales, Marketing, or Data Ops). Most weeks you spend ~70–80% of your time actually building: writing, testing, and shipping code and configurations that power automations and AI-powered agents on HubSpot’s platform.
You are the primary GTM Engineering partner for at least one motion or area in your customer team. You deeply understand how that motion works in practice, design focused POC/MVP experiments, and own end-to-end delivery of agents and automations that improve revenue, efficiency, or productivity for that function.
Ops leaders and partners own the “what”; you make the “how” real in production. You don’t stand up your own platform or parallel product org; you build on top of core HubSpot, Flywheel, or 3rd party platforms, proving what works in your domain and partnering with your leadership to scale winning ideas.
Design and deliver POCs/MVPs end-to-end
Run small discovery loops with your embedded pod (Ops leaders, BSAs/Ops Analysts, Product partners) to understand workflows, quantify impact, and list assumptions before you build anything.
Choose the lightest solution that could work—config, report, workflow, automation, or a simple single-purpose agent—and evolve it based on real usage and outcome data.
Build and evolve agents on HubSpot’s AI platform
Combine models, prompts, retrieval, and tools for specific GTM use cases in your area (for example, success coaching for CSMs, lead handling for Sales, renewal outreach for Contract Management).
Use our AI platform and in-product AI tools when they are the simplest safe way to solve a problem, and partner with Intelligent Automation Engineers when you need capabilities from third-party platforms they own.
Implement automations and integrations across the GTM stack
Build and operate medium-complexity automations, integrations, and agents across HubSpot CRM objects/properties, workflows, sequences, chatflows, ticketing, routing, reporting, and approved tools like Workato.
Partner with senior team members to design parameterised recipes and workflows so flows and agents can be adopted by multiple teams or individuals solving similar problems for their respective domains of ownership.
Instrument, measure, analyze; add basic logging and monitoring so you and your stakeholders can see how an agent or automation behaves in production.
Operate what you build with solid engineering hygiene
Follow BRAVE and other guardrails to ship thin slices behind flags or limited audiences, with clear rollout and rollback plans.
Add acceptance / end-to-end tests for critical paths and basic coverage for failure and edge cases, including evals for AI systems.
Refactor, simplify, and sometimes delete: consolidate flows, agents, and recipes so the footprint you ask your pod to support stays small, understandable, and reliable.
Partner with your stakeholders
Work with Ops leaders, BSAs/Ops Analysts, and GTM teams to clarify problems, success metrics, and constraints for a focused set of workflows in your area.
Break work into small increments (POCs → MVPs → hardening) and keep stakeholders updated on progress, trade-offs, and observed impact.
Act as the main GTM Engineering contact for your area
Show up as a reliable partner, not just a ticket owner: write clear tickets and specs when you need support from adjacent team, and respect ownership boundaries.
Coordinate with local Ops, Sales, Marketing, or CS leaders when rollouts affect reps or customers, and adjust scope when needed.
Contribute to patterns and the GTM Engineer guild
Turn successful experiments into reusable patterns with examples and short docs so other GTM Engineers, Ops Analysts, and BSAs can adapt them for their own use cases.
Share learnings back into the GTM Engineer guild so embedded engineers in other teams can move faster on the next wave of experiments.
You already operate as a senior IC for your team or function: you are the person your pod turns to when a GTM workflow is complex, ambiguous, and needs a concrete automation or agent shipped. You spend most of your time in the build and debug loop.
Hands-on builder experience
3+ years of hands-on engineering / builder experience—for example: software engineer, internal tools engineer, automation engineer, or very technical BSA/Ops engineer—where you shipped and supported production systems or automations.
Applied AI / automation
You have either:
Shipped at least one AI- or agent-style feature that real users used, or
A strong track record building production systems and a clear interest in applying AI in workflows.
Technical fluency across low-code + code
Proficient in Python, SQL, and working with REST/RPC APIs and JSON; comfortable navigating GitHub and service catalogs to stitch together solutions across systems.
Comfortable with Java and REST troubleshooting and with iPaaS like Workato/Zapier/n8n; able to debug integrations and automations end-to-end with limited support.
Business and experimentation skills
Understands core GTM metrics (for example, GRR, UUS, CSAT, pipeline velocity, conversion, rep productivity) and connects experiments directly to those levers.
Consistently designs and delivers measurable POCs/MVPs that influence local GTM priorities and demonstrate clear before/after impact.
Owner mindset and accountability
You treat every automation and agent you touch as your responsibility until it is stable, monitoring logs, dashboards, and tickets and fixing issues quickly or pulling in the right partner when you’re stuck.
You define expected usage and outcomes before you build, check those numbers after launch, and decide whether to iterate, roll back, or kill the work based on data and customer feedback.
Bias for small, safe, high-impact changes
You break work into small, shippable slices, ship behind flags or to limited audiences, and learn from real behavior instead of waiting for a big launch.
You push back on low-impact requests—even when they sound urgent—and use simple impact-vs-effort thinking to decide what you do next and explain those decisions in plain language.
Trusted collaborator across teams
You communicate clearly with both technical and non-technical audiences, translating between GTM needs and technical constraints without drama.
You are the main GTM Engineering contact for at least one domain area within our GTM motion, and a trusted partner to local Ops and GTM leaders on team- and function-level initiatives.
Adaptable, learning-oriented builder
You adjust quickly when tools, priorities, or org structures change; you learn new AI and agent capabilities and try them on low-risk use cases before recommending them widely.
You prefer small, fast iterations over big-bang projects and are willing to kill your own ideas when data or users tell you they’re not working.
We know the confidence gap and impostor syndrome can get in the way of meeting spectacular candidates, so please don’t hesitate to apply — we’d love to hear from you.
If you need accommodations or assistance due to a disability, please reach out to us using this form.
At HubSpot, we value both flexibility and connection. Whether you’re a Remote employee or work from the Office, we want you to start your journey here by building strong connections with your team and peers. If you are joining our Engineering team, you will be required to attend a regional HubSpot office for in-person onboarding. If you join our broader Product team, you’ll also attend other in-person events, such as your Product Group Summit and other gatherings, to continue building on those connections.
If you require an accommodation due to travel limitations or other reasons, please inform your recruiter during the hiring process. We are committed to supporting candidates who may need alternative arrangements
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