Sales Development Representative

Shadeform•Charlotte, NC

12d•Remote

About The Position

As an SDR at Shadeform, you'll build and feed a qualified pipeline into the sales team through both outbound prospecting and inbound lead management. The role combines market intelligence, technical awareness, and structured outreach to find and engage the right buyers — while making sure no inbound opportunity slips through without a timely, high-quality response.

Requirements

1–3 years in an SDR, BDR, or similar outbound sales role, ideally selling a technical product to a technical buyer.
A real prospecting habit — you're comfortable running email, social, and phone outreach, and you write messaging that lands.
Enough technical fluency to hold your own in a conversation about AI infrastructure, or the appetite to get there fast.
Discipline with a CRM and your pipeline. You log activity as you go and treat clean data as part of the job, not an afterthought.
Comfort qualifying against frameworks — validating pain, budget, timing, and technical fit — and knowing when to route a lead up versus run with it yourself.
Hands-on experience with prospecting tools like Apollo or LinkedIn Sales Navigator (or the ability to pick them up quickly).

Nice To Haves

Experience selling into AI labs, infrastructure teams, or developer-heavy organizations.
Familiarity with the GPU or cloud market — neoclouds, data center capacity, SKUs like H100 and H200.
A track record of experimenting with AI-driven or automated prospecting workflows.

Responsibilities

Own end-to-end research for the verticals you identify as most promising — mid-market and early-stage startups, enterprise, AI labs, GenAI companies, VFX and rendering, bioinformatics, and others.
Build accurate, enriched prospect lists using tools like Apollo, Unify, Crunchbase, and LinkedIn Sales Navigator.
Map org structures to find decision-makers and budget holders (CTO, Head of Infrastructure, ML Lead, Ops).
Track GPU capacity trends, ecosystem movements, and gaps that point to product opportunities.
Feed that intelligence back to the team to shape messaging and campaigns.
Run multi-channel campaigns across email, social, and phone, with messaging tailored to each prospect's stack and scaling needs.
Write technically aware messaging that shows real understanding of AI infrastructure pain points — GPU scarcity, latency, scaling bottlenecks, market shifts.
Book a minimum of 30 discovery calls per month with qualified buyers, plus platform registrations.
Deliver at least 5 qualified opportunities per month to the AE team that convert into pipeline.
Own the inbound lead queue as your first priority — no inbound lead goes uncontacted beyond 4 business hours.
Respond to every inbound lead with a personalized, technically aware first touch that reflects their context, not a generic template.
Qualify inbound leads with the same frameworks you use for outbound — validating pain, budget, timing, and technical fit before routing.
Triage accurately: route high-value or complex opportunities to the Senior AE and Head of Sales with full context, and self-manage smaller or early-stage leads through to qualification.
Track and report on inbound volume, source quality, and conversion rates so the GTM team can see which channels perform best.
Log every inbound lead in the CRM on receipt, with source, initial context, and next step recorded.
Use our sales frameworks and playbooks to validate pain, budget, and timing, and to think creatively about how we onboard customers for the long term.
Understand each customer's technical context — workload type (LLM training vs. inference), GPU requirements, current deployment scale, and who to engage to support them over time.
Hand off qualified opportunities to the AE team with complete context and a full set of qualification questions answered, so they walk into the meeting knowing what the customer needs.
Log all activity, insights, and engagement data cleanly in the CRM.
Continuously optimize outreach methods and sequences based on performance data.
Collaborate with marketing, GTM, and the AE team on outbound content — case studies, email hooks, and campaign angles.
Experiment with AI-driven prospecting tools and automation to scale efficiency across the GTM team.
Proactively identify and vet new GPU cloud providers and capacity sources to close supply gaps against active pipeline — particularly for high-demand SKUs (H100, H200, B200/B300) where existing supplier inventory can't meet a deal's requirements or timeline.
Monitor the GPU supplier landscape — neoclouds, regional data centers, emerging capacity providers — to build a bench of vetted, ready-to-activate providers before they're needed, rather than sourcing reactively once a deal stalls.
Work directly with Sales and the founding AE team to understand unmet requirements on live deals (region, SKU, node count, SLA terms, timeline) and translate them into targeted outreach to prospective suppliers.
Run initial vetting on new providers — capacity, pricing competitiveness, SLA terms, data center tier and certifications, network performance — before looping in Sales or Ops for deeper diligence.
Keep accurate, up-to-date records of prospective and onboarded providers in Airtable (Supplier Inventory), including capacity, pricing, lead times, and relationship status.
Flag supply constraints or emerging shortages to Sales and leadership early, so pricing and deal strategy can adjust before they become blockers.
Build relationships with provider-side BD and sales contacts to create a repeatable sourcing channel rather than one-off outreach per deal.