growthroles

AI GTM Engineer

SigNoz signoz.io Open · verified Sep 24, 2026
Remote India Full-time Mid-level Solutions & Sales Engineering

At a glance

Mid-level Solutions & Sales Engineering role at SigNoz. Remote, India · full-time.

Pay not stated

RoleSolutions & Sales Engineering
SeniorityMid-level
LocationIndia
WorkplaceRemote
EmploymentFull-time
PostedJul 20, 2026 · 2mo ago
Role brief

Growth Roles summary, based on the employer's posting.

What you'll do

  • Build ranked HubSpot and Slack queues from signup, usage, expansion, and win-back signals
  • Create BigQuery reporting that connects signups, SQLs, and closed-won outcomes
  • Automate CRM routing, lifecycle stages, data cleanup, and account-health alerts
  • Use LLMs, agents, and connectors for enrichment, research, scoring, and personalization
  • Run GTM tooling, email journeys, ABM lists, experiments, and ad hoc analysis

What you bring

  • Strong SQL skills plus the ability to build pipelines in BigQuery or a comparable warehouse
  • Working ability in Python or TypeScript and experience using APIs, especially HubSpot APIs
  • A practical view of which account signals deserve sales attention, tested against closed business
  • Experience partnering with sales or growth teams and learning directly from representatives
  • Ability to work independently and asynchronously with some overlap with US hours

Who this fits

You’ll suit a hands-on operator who can move between data pipelines, CRM automation, campaign workflows, and sales questions. The role is remote in India and expects independent execution, with some working-hour overlap with the US.

From the employer

AI GTM Engineer

About the role

We’re looking for an AI GTM Engineer to own the systems, data, and processes behind our marketing engine.

This is a hands-on role. You’ll work across Marketing, Sales, Product and Growth to make sure our campaigns run smoothly, our data is reliable, and we’re continuously improving conversion across the funnel.

You should be equally comfortable building a dashboard, fixing an email workflow, creating an account list, and figuring out why a conversion rate dropped.

What you'll build

  • Signal queues for sales. Define and ship signals such as ICP signups, usage spikes, expansion and win-back triggers, delivered to reps as ranked queues in HubSpot and Slack.

  • Customer health and alerting. Build usage and billing-spike alerts so CS and Sales act on changes in paying accounts.

  • A trusted funnel. Build one source of truth for signup to SQL to closed-won in BigQuery, trusted by every GTM lead.

  • AI-native GTM workflows. Use LLMs and agents for enrichment, research, scoring and personalization, and measure how accurate they are.

  • CRM automation. Automate lead routing, lifecycle stages and data hygiene end to end, with zero manual lead assignment.

  • Build a self improving GTM system using LLMs and connectors to data source

You'll also own

  • GTM tooling across HubSpot, Customer.io, Clay, Lemlist and n8n

  • Email journeys for prospects, product users and customers, including segmentation and experiments

  • Account lists, enrichment and measurement for ABM and outbound campaigns

  • Ad hoc analysis for Sales and Marketing data

Who would be a good fit

  • Strong SQL. You're comfortable in BigQuery or a similar warehouse and build pipelines yourself.

  • You can write code (Python or TypeScript) and work with APIs, especially CRM APIs like HubSpot's.

  • You define signals, not just implement them: you have a view on what makes an account worth calling, and you check that view against what actually closes.

  • You've worked closely with sales or growth teams, or you're eager to sit with reps and learn what they need.

  • You ship scrappily on your own, without needing a data team around you.

  • You can work async with some overlap with US hours.

Bonus points

  • Experience at a PLG, developer tools, infrastructure or open-source company

  • Hands-on experience with HubSpot, Clay, Customer.io or n8n

  • You've built entity resolution or enrichment pipelines (for example, domain or IP to company)

  • You've shipped LLM or agent workflows in production and measured their accuracy

  • You've used product usage data to drive sales or expansion

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