🚨 We’re Looking for a Full-Time Automation / GTM Engineer (Collaborative Role) 🚨 We’re an early-stage company at RLG Property Solutions, building AI-driven automation systems to support the mid-term, insurance, and corporate housing space. Our goal is to intelligently connect furnished property inventory with verified housing demand, especially for insurance placements and temporary relocation by automating inbound request handling, intelligent matching, and clean GTM workflows. We’re looking to collaborate full-time with someone who truly understands modern automation, not just tools, but scalable, reliable system design. This is a long-term opportunity to be part of the core team. As the systems you help build drive more placements, demand, and revenue, compensation will scale accordingly. We believe in aligning incentives with impact and growing together as the company grows. What We’re Building • Inbound-first automation using a self-hosted n8n setup (Hostinger) • AI agents that: Monitor inbound emails for new requests Extract structured intent and requirements Match against a live inventory database Surface results for human review before any response • Clean, scalable handoffs from inbound → matching → review → response • Validation-first systems (correctness > speed > scale) GTM / Outreach (Secondary, Conservative) Low-volume outbound email (tools like Instantly / Plusvibe)
Strong focus on deliverability, inbox health, and domain rotation
Long-term nurturing sequences, not spammy blasts
Credit efficiency and discipline matter
What We’re Looking For Strong experience with automation tools (n8n, Make, Zapier, or similar) Comfort with AI-assisted workflows (prompting, parsing, matching logic) Familiarity with Clay or similar enrichment / GTM tools Understands inbox architecture, warm-up, and deliverability basics
Thinks in systems and phases, not hacks
Comfortable working in early-stage, collaborative environments
What Matters Most Clear thinking Practical execution
Ability to build something stable and unbreakable first, then scale
If this sounds like you and you want to collaborate long-term on meaningful automation, reach out or comment below. Let’s build this the right way.
Part-Time / Short-Term → Potential Ongoing Partnership (Clay / GTM) Hi everyone, I’m Rafael, founder of RLG Property Solutions. We’re a startup working with insurance, relocation, and temporary housing companies to connect verified housing demand with furnished inventory. We’re now looking for one strong partner we can work with to help us scale lead generation in a smart, cost-efficient way. What we’re looking for: • Someone experienced with Clay who understands ICP-driven workflows • Strong focus on credit efficiency (validation first, enrichment later) • Ability to help us: Validate and clean existing company/contact data Identify high-quality decision-adjacent leads Build repeatable, scalable workflows as volume grows What matters most to us:
Cost-conscious execution (we’re a startup)
Quality over volume
Long-term collaboration > one-off scraping
Engagement:
Start part-time / short-term
Paid hourly
Opportunity to grow into an ongoing partnership as we scale
If this aligns, please DM me with:
Your Clay experience
How you approach credit efficiency
Availability
Thanks!
Thanks for the response. Happy to clarify. We are specifically looking to connect with relocation and temporary housing decision makers, not field adjusters or examiners. Our ideal contacts are people who control or influence housing placements and partner relationships, such as: Relocation Specialists Housing Coordinators Corporate Housing Managers Account Managers handling ALE or displacement housing Vendor Managers for temporary housing networks Claims Managers who oversee housing placements at a program level The companies we want to prioritize include: Relocation and temporary housing providers like ALE Solutions, CRS Temporary Housing, Alacrity, Sedgwick, Crawford, and similar firms Insurance carriers and TPA organizations that manage displacement or loss of use housing programs Corporate housing providers and mid term housing networks that place guests for 30 to 180 day stays The main challenge right now is filtering out high volume operational roles like adjusters and examiners so credits are only used on roles that can actually approve partnerships or send placement opportunities. What we want help with is tightening job title logic, seniority signals, and company type filters so we consistently surface relocation partners and housing decision makers across the US. Happy to share example titles or target companies if that helps dial this in further.
Hey Bo (., thanks for checking in. I’m at the stage where I’m trying to build out a scalable automation in Clay to identify and reach the right roles across specific companies in this category. The goal is to reliably find and structure a large list (ideally 1,000+ contacts across the U.S.) that are actually relevant decision-makers or strong connectors for what we’re doing. Where I’m getting stuck is making sure I’m structuring the table, filters, roles, and enrichment logic the right way so the data stays clean and exports properly into Instantly without breaking downstream. I want to be confident that what I’m building now will scale, not just work for a small batch. Any guidance on best practices here or how you’d recommend approaching this at scale would be super helpful.
Hey Bo (. thanks so much for the clarity, really appreciate it. That makes sense. I’d definitely be interested in working with a Clay Expert for a bit more hands-on guidance, especially to make sure I’m structuring the table + Instantly export correctly. Could you point me to where I can find or book a Clay Expert? Once I get a bit more hands-on experience and see the full flow end-to-end, I promise I won’t be a bother I pick things up quickly and just want to make sure I’m setting this up the right way from the start. Thanks again 🙏
Human support please
I am still experiencing difficulties / challenges
This is super helpful — thank you. I’m aligned with this approach and I’m still intentionally pre-scale. Right now: I have a Find People table populated I’m generating rough-draft intro emails in Clay to validate tone/positioning I’m manually reviewing outputs and not pushing anything to Instantly yet
I want to lock in role coverage + table structure before wiring automation
My immediate next goal is to confirm: I’m not missing key decision-makers or connectors My current columns are the right schema to push into Instantly
Whether it makes sense to add validation/conditional logic now or wait until volume increases
Before moving to the API-based Clay → Instantly setup, is there a recommended “v1 ready” checkpoint you’d suggest (e.g. specific validations, column structure, or row volume to test)? Happy to follow whatever best-practice sequence you recommend here. Appreciate the guidance.
Thanks for the detailed response — that’s helpful. To give more context on where I’m at: I currently have a Find People table built and populated, and I’m generating rough-draft intro emails inside Clay to preview tone and positioning. I’m intentionally still in a validation phase — not sending yet — and want to make sure a few things are dialed in before I scale or connect Instantly. My goals right now are: Confirm I’m capturing all relevant decision-makers and connectors (account managers, vendor managers, housing/relocation coordinators, etc.) and not missing key roles Validate my table structure and enrichment logic so I’m not over- or under-filtering Sanity-check that my Clay outputs are clean and ready to export to Instantly once I’m confident
Understand the best next step for wiring Clay → Instantly (manual export vs API) once this v1 is locked
I’m not stuck on API key creation itself — more on workflow validation and readiness to scale. If there’s a recommended best-practice checklist, walkthrough, or next-step guidance for this phase, that would be really helpful. Appreciate the support.
