AI Operations Engineer
We are a well-funded, early-stage startup seeking a pragmatic, AI Operations Engineer to build and own the internal tooling, automations, and AI agents that make Reindeer itself a more productive company.
This is a first step into the architecture and strategy of AI-driven automation for large-scale enterprise environments.
Key Responsibilities:
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AE sales-cycle accelerator - pre-call prep, account research, follow-up drafts, CRM hygiene.
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Security questionnaire and RFP/RFI agent - auto-respond to security questionnaires in prospect vendor onboarding.
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POC scoping and proposal agent - turn discovery notes and call transcripts into proposals and scoped POC plans.
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Account expansion and renewal signals - monitor usage and customer signals on enterprise accounts; surface expansion opportunities and renewal risk.
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Case study and reference agent - extract reference-worthy quotes and metrics from customer calls; manage the reference inventory.
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Soundbites-to-social, meeting follow-up tracker, competitive research tool.
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Internal billing app - usage tracking, invoicing, and dunning.
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Procurement and vendor onboarding tool - intake, security review, contract storage, approval routing.
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Agent ops dashboard - monitor customer-facing agent runs (errors, latency, cost).
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Internal compliance agents - verify customer requirements: security, open source licenses, DPAs.
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Profitability dashboard - agent cost vs. revenue with surfaced optimization opportunities.
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Own workstation, network, identity, and SaaS administration for the company.
- 2+ years of full-stack engineering, with end-to-end ownership of internal tools, integrations, or automation systems.
- Track record of shipping production-quality internal software in a fast-moving environment.
- Proficiency in Python and TypeScript/Node required; we build our frontend in Svelte, so comfort with lightweight web UIs is a strong plus.
- Hands-on with SaaS APIs (Salesforce/HubSpot, Ashby, Rippling, NetSuite/QBO, Stripe, Slack, Notion).
- Practical experience with LLMs and AI agents - prompting, evaluating, and operating in production-adjacent workflows.
- SQL (PostgreSQL, MySQL); familiarity with NoSQL/Vector DBs.
- Cloud deployment on AWS, GCP, or Azure; OAuth2/JWT and secure integration practices.

