Joseph Clark
Technical Account Manager · AI Solutions · Sales Engineer
Remote · Clients + systems + practical AI
I sit between customers and product.
Background: Accenture (client operations / finance) → Sales Engineer at Halcyon → Account Manager at Trevera → freelance software & AI work for real operators.
That path means I can:
- own account health, renewals, expansions, and escalations
- run demos/POCs and translate product ↔ buyer language
- implement AI automation where it removes friction, not where it creates theater
I’m looking for remote roles as Technical Account Manager, AI Solutions Consultant, Customer Success (AI/SaaS), or mid-market Sales Engineer.
| Role | Org | Years |
|---|---|---|
| Freelance Software Engineer & AI Builder | Independent (client + product work) | 2024 – Present |
| Account Manager | Trevera | 2023 – 2025 |
| Sales Engineer | Halcyon | 2022 – 2023 |
| Client Operations Analyst | Accenture | 2021 – 2022 |
All remote.
Education: M.S., IT Management — Western Governors University (2023–2024) · B.S., Finance — University at Buffalo (2020)
I take on scoped builds where commercial context matters as much as code:
- Clinic / operator automation — lead handling, booking, and follow-up workflows; CRM as source of truth; discovery → build → handoff so non-technical teams can run it
- Investor-facing web systems — production sites and internal tools for small public / OTC companies (clean IR presence before filings)
- GTM enablement tools — TypeScript/Python services and Next.js apps used in live outbound and account workflows
Operating principle: ship something an account team can defend in a QBR, not a demo that dies after the call.
I treat AI as delivery infrastructure, not a personality.
Agent systems & evals
- Multi-agent workflows for research → draft → quality gate → action
- Eval / harness thinking: artifact-first checks, failure modes, human gates before risky actions
- RAG and tool-using agents for account/ops contexts (not toy chat wrappers)
Applied GTM agents
- BDRclaw — open-source AI BDR patterns: prospect research, gated outreach drafts, reply classification, CRM sync across email/SMS/LinkedIn rails
- Focus on control flow, quality gates, and auditability — the parts employers care about when AI touches customers
Selected recognition
- **LabLab.ai AI Agents Hackathon — autonomous multi-agent pipeline; recognized for effective agent prompting
I’m less interested in “AI for AI’s sake” and more in: Does this reduce implementation friction, protect the account, and survive production?
|
Open patterns for an AI BDR: research, draft/gate outreach, classify replies, book meetings, keep CRM authoritative. Built to show safe agent design for customer-facing workflows. |
Hands-on AI automation for clinics and operators: multi-channel workflows, CRM-centered state, and handoffs non-technical teams can run. Implementation included. |
Client & GTM — account management · sales engineering · demos/POCs · renewals/expansion · CRM discipline · stakeholder communication
AI leverage — agent workflows · automation · RAG · eval/harness thinking · practical LLM tooling for delivery
Build — TypeScript · Python · JavaScript · Next.js/React · Node · APIs · SQL · Git
Languages — English (native) · Spanish (C1) · Italian (B1) · Portuguese (B1)
Open to remote TAM / AI Solutions / CSM / Sales Engineer roles · linkedin.com/in/josephc9

