
AI • Telecommunications • Enterprise
Dialpad is an AI-powered customer communication platform designed to facilitate and streamline business communications. It offers a range of cloud-based solutions for customer support, contact centers, and sales outreach, integrating AI technology for automated note-taking, in-call coaching, and productivity insights. Dialpad is used across various industries such as retail, insurance, technology, and more, to optimize sales, support teams, and enhance customer experiences. By providing tools for better communication and customer interactions, Dialpad empowers businesses worldwide.
1001 - 5000 employees
Founded 2013
📡 Telecommunications
🏢 Enterprise
💰 $170M Series F on 2021-12
October 9
🇺🇸 United States – Remote
⏰ Full Time
🟡 Mid-level
🟠 Senior
⛑ DevOps & Site Reliability Engineer (SRE)
🦅 H1B Visa Sponsor

AI • Telecommunications • Enterprise
Dialpad is an AI-powered customer communication platform designed to facilitate and streamline business communications. It offers a range of cloud-based solutions for customer support, contact centers, and sales outreach, integrating AI technology for automated note-taking, in-call coaching, and productivity insights. Dialpad is used across various industries such as retail, insurance, technology, and more, to optimize sales, support teams, and enhance customer experiences. By providing tools for better communication and customer interactions, Dialpad empowers businesses worldwide.
1001 - 5000 employees
Founded 2013
📡 Telecommunications
🏢 Enterprise
💰 $170M Series F on 2021-12
• Lead pilots end-to-end: Scope success criteria, configure sandbox environments, and iterate rapidly to hit ROI targets in ≤ 90 days. • Design agent workflows: Author multi-step prompts, retrieval pipelines, and decision logic that plug into CRMs, ERPs, and custom APIs via our MCP framework. • Build secure integrations: Stand up data connectors and authentication flows (OAuth 2.0, SCIM, SAML) that give agents real-time context while meeting SOC 2 & HIPAA controls. • Operationalize at scale: Containerize and deploy agents on Kubernetes or customer VPCs; set up monitoring, A/B evaluation, and guardrails for hallucination and PII leakage. • Drive feedback loops: Surface customer insights to Product & Research; influence roadmap priorities around tooling, guardrails, and vertical templates. • Enable self-sufficiency: Deliver workshops, runbooks, and best-practice playbooks so clients can extend and govern agents post-go-live.
• 4+ years in forward-deployed engineering, solutions architecture, or technical consulting for SaaS/AI products. • Proficiency in Python, Go, JS/TS plus hands-on experience with LLM frameworks (LangChain, RAG, vector search). • Cloud-native skills across AWS/GCP/Azure; comfortable with Docker, Helm, Terraform. • Strong communicator who can whiteboard with engineers at 10 AM and brief the C-suite at 4 PM. • Thrive in ambiguity; bias for action and a “customer-in-control” mindset. • Telephony stack knowledge (WebRTC, SIP, Twilio). • Experience deploying chatbots or voice bots at >10K daily conversations. • Contributions to open-source AI agent frameworks.
• Competitive benefits and perks • Robust training program
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