GTM Applications Engineer

GTM AI Applications Engineer

Context & Impact:
This is a backfill role within Lansweeper's Revenue Operations team, built for someone who wants to spend meaningful time designing and building AI agents — not just maintaining systems. As a GTM Applications Engineer (AI Agents & Integrations), you'll own the technical layer connecting our go-to-market application stack while actively identifying where AI can eliminate admin overhead, consolidate tooling, and automate GTM processes end-to-end.

In this version of the role, you won't wait to be told where AI fits — you'll proactively find it, prototype it, and build it. The stack is your canvas; agents and skills are how you leave your mark.

Challenge:
The main challenges you'll face are:

• Breadth across platforms — the GTM stack spans Gainsight, Gong, Zoom Info, Zoom Phone, Docu Sign, Salesforce, and more. You'll need to stay technically sharp and agile across all of them, adapting quickly as each platform evolves.

• Agentic work at the frontier
  . Building and orchestrating AI agents, whether in Workato, Lang Chain, Claude managed agents, or Salesforce Agentforce, is still emerging practice. You'll be working without a full playbook, which requires comfort with ambiguity and a bias for experimentation.

• Self-directed identification of AI opportunities — rather than waiting for direction, you'll be expected to surface process gaps, evaluate their AI-fit, and propose solutions. That requires both technical fluency and strong GTM process understanding.

Key Responsibilities:

• Own configuration, administration, and troubleshooting for the GTM application stack.

• Build and maintain integrations and data pipelines between GTM applications and Salesforce (e.g., Snowflake to Gainsight).

• Proactively identify GTM process areas where AI agents, automation, or AI-assisted workflows can reduce admin burden, consolidate tooling, or improve data quality.

• Design, build, and deploy AI agents across the stack, using whichever platform fits the job (Workato, Lang Chain, Claude managed agents, Salesforce Agentforce, or equivalent), from scoping and prompt engineering through orchestration and into production.

• Monitor observability for deployed agents. Track what they do in production, catch failures or drift early, and iterate based on real usage.

• Build human-in-the-loop checkpoints for agentic workflows. Decide where an agent should escape to a person instead of acting on its own, and design that approval or fallback path.

• Provide technical guidance and drive improvements across GTM systems projects, becoming the senior technical voice for AI integration within the stack.

• Take on lighter Salesforce administration and configuration tasks (fields, flows, permissions) alongside the Salesforce team.

• Evaluate and onboard new AI tools and GTM applications as the stack evolves, staying ahead of what's available and what's production-ready.

• Partner with GTM Ops, Sales, and Customer Success stakeholders to translate process needs into scalable, AI‑augmented technical solutions.

Key Requirements:

Hard skills:

• 2–4 years in a technical applications, systems administration, or integrations role within a SaaS environment.

• Hands‑on experience building with AI agents or AI‑assisted tooling — production deployments, internal pilots, or substantive personal projects.

• Practical prompt engineering skills — able to design, test, and iterate prompts within AI platforms to produce reliable, production‑grade outputs.

• Hands‑on experience with integration/orchestration platforms such as Workato, Zapier, or similar. Most agent orchestration in this role runs through here.

• Hands‑on experience building and deploying AI agents on any agentic platform (examples: Lang Chain, Claude managed agents, Salesforce…