GTM Engineer

If interested, please email your resume to jobs (at) meritholdings.com

and respond to the following questions:

What’s the last new skill you learned for fun and how did you tackle it?
What accomplishment didn’t make it on your resume but tells a story about you?
What AI/GTM workflow are you most proud of? Describe it (without breaking any NDAs).

Merit is a purpose-driven software holding company focused on forging long-term partnerships with hyper-

specialized vertical market software businesses. Merit’s mission is to be a trusted partner for business owners

seeking a unique alternative to traditional private equity—offering lasting partnership and continued

investment in people, products, customers, and values. We measure success in decades, not quarters.

We are building a world-class investing and operating organization comprised of former operators and

investors with deep experience scaling vertical software companies. Our partner companies operate

independently while benefiting from shared expertise, systems, capital, and community.

We are actively recruiting a Go-to-Market (GTM) Engineer to help design, operate, and evolve the AI-first

systems that power Merit’s investment sourcing efforts and portfolio GTM enablement.

This role sits at the intersection of sales, marketing, and technology. You will focus on connecting tools,

configuring workflows, building automations, and ensuring system reliability across a modern GTM

stack—using LLMs and AI-native workflows as a default. You will work closely with the existing team to

translate strategy into scalable, repeatable systems that create leverage—without stifling operational

autonomy.

Operating Philosophy

Design and operate GTM systems that run reliably without manual intervention, rather than executing individual campaigns or one-off tasks.
Build automated pipelines that systematically generate, enrich, prioritize, and route opportunities, rather than relying on manual lead sourcing.
Use AI as a first-class component of workflows (research, classification, personalization, summarization, routing, and QA), not as an afterthought.
Optimize for durability, observability, and data integrity, ensuring systems continue to perform as strategy, volume, and tooling evolve.
Treat GTM workflows as long-lived assets that compound in value through iteration, documentation, and reuse.

One Role. Two Exciting Verticals

Investment Sourcing Systems (Primary)

The primary objective of this role is to operate and continuously evolve Merit’s AI-first investment

sourcing engine, enabling the firm to systematically identify, research, engage, and build long-term

relationships with high-quality vertical software businesses at scale.

We treat sourcing as a product: built on durable systems, automation, and AI-driven insight rather than

manual workflows.

Responsibilities

Own the configuration, reliability, and evolution of Merit’s AI-first sourcing GTM systems, including CRM, sequencing, enrichment, orchestration, and analytics tooling—ensuring workflows scale cleanly as sourcing coverage and strategy evolve.
Design and operate AI-native sourcing workflows across the full lifecycle, including:
- Target universe creation and maintenance
- Data enrichment and entity resolution
- LLM-assisted research, classification, and segmentation
- AI-supported prioritization and routing signals
- Automated outreach sequences and follow-ups
- Response handling, relationship tracking, and conversion to diligence
Operate and improve AI-assisted sourcing outreach, leveraging LLMs to generate high-quality, personalized messaging while maintaining strong guardrails around quality, accuracy, and brand consistency.
Build and maintain LLM-powered workflow components that improve efficiency and quality, such as:
- automated company/founder research and summarization
- enrichment QA and inconsistency detection
- tagging and classification for vertical/ICP fit
- message personalization inputs and structured briefs
- CRM note generation and meeting preparation summaries
Partner with data science and investing stakeholders to translate investment theses into operational signals, and operationalize scoring outputs inside workflows (segmentation, routing, sequencing, dashboards). You do not need to build ML models, but you should be comfortable integrating AI outputs into production workflows.
Ensure world-class data quality, reliability, and transparency across the sourcing stack, including deduplication, enrichment confidence, lifecycle definitions, routing logic, and auditability—using AI where it improves accuracy, explainability, or throughput.
Build instrumentation and visibility into sourcing performance and system health, including universe coverage, outreach activity, response rates, meeting rates, conversion to diligence, cycle times, and failure modes.
Continuously identify friction points, bottlenecks, and failure modes in the sourcing funnel; diagnose root causes using system behavior and data; and ship iterative improvements to automation and AI workflows.
Translate evolving investment strategy into durable systems, working with the existing team to reflect new verticals, themes, and learnings through AI-assisted automation and workflow changes rather than manual process.
Document sourcing systems, prompts, automation logic, and operating principles, ensuring AI workflows are understandable, repeatable, testable, and resilient as the platform grows (including prompt/version management, quality checks, and guardrails).

Portfolio GTM Enablement (Secondary)

Support Merit’s portfolio growth efforts by helping portfolio companies adopt pragmatic, AI-first GTM

systems and automation, often starting from very simple foundations.

Responsibilities

Partner with portfolio leadership teams to assess and improve GTM systems, including CRM setup, lifecycle definitions, automation, reporting, and data quality—introducing AI where it improves clarity, throughput, or consistency.
Adapt and deploy Merit-proven AI-first workflows and automation patterns to portfolio-specific use cases, balancing standardization with flexibility across stages and verticals.
Collaborate with the portfolio growth team to turn workflows into repeatable assets, creating reusable templates, prompts, playbooks, and system patterns that can be deployed efficiently across companies.
Support adoption of AI-native GTM workflows such as:
- AI-assisted account research and prospecting briefs
- automated data cleanup, enrichment QA, and CRM hygiene
- AI-assisted messaging personalization and sequencing
- automated call/meeting summaries and next-step routing
- pipeline visibility and “what changed” dashboards
Encourage cross-portfolio learning by sharing successful AI workflows, systems patterns, and operational insights to drive platform-level leverage.

Qualifications

Core Experience

Experience in GTM systems, growth operations, revenue operations, or sales/marketing automation
Strong comfort operating CRM systems (e.g., Attio, HubSpot, Salesforce) and sequencing tools
Hands-on experience with automation and orchestration tools (e.g., n8n, Make, Zapier)
Demonstrated comfort with LLMs and AI tools (e.g., GPT, Claude, Gemini) and experience incorporating them into automated workflows
Experience working with enrichment, data providers, and API-driven tools
High bar for data quality, system reliability, documentation, and operational rigor

Nice-to-Have

Familiarity with APIs, webhooks, and basic scripting (Python or JavaScript)
Experience with prompt design and management (testing, iteration, guardrails, evaluation)
Experience working alongside engineers and data scientists to ship system improvements
Exposure to agentic frameworks and orchestration patterns (multi-step automation, tool use, MCP-style integrations)
Previous experience in a formal software developer/engineer role is not required, but a proven ability to grasp and apply technical concepts to business problems is essential

How You’ll Be Successful

You turn complex GTM workflows into clean, reliable, AI-first automated systems
You reduce manual effort while increasing sourcing and outreach quality and consistency
You make AI workflows observable, testable, and trustworthy through instrumentation and guardrails
You improve visibility and trust in GTM data and metrics
You help turn internal GTM systems into reusable AI-first assets for the portfolio
You operate with ownership, curiosity, and a long-term, compounding mindset