Jobs at Dialpad

Build scalable automated testing frameworks and test strategies for AI-driven contact center products. Develop functional, regression, UI, API, database, capacity, security, and performance tests; analyze failures; define quality KPIs; participate in design reviews; integrate testing into CI pipelines; and mentor engineers. The role requires validating non-deterministic AI behavior and enterprise-scale SaaS reliability across microservices.

Own production systems for real-time speech AI, including model serving, self-hosted inference, third-party API integrations, scaling, reliability, observability, release infrastructure, and failover. Build backend services and deployment workflows that meet latency, uptime, quality, and cost objectives. Partner with speech, MLOps, platform, telephony, and product teams while providing technical leadership and mentorship.

Own end-to-end quality for Dialpad’s AI voice-agent features by developing test automation, evaluation frameworks, observability tooling, and CI/CD quality checks. Test frontend, backend, API, audio, text, orchestration, and tool integrations, including performance, reliability, safety, hallucination, and bias risks. Partner with AI and development teams on prompts, models, and evaluation strategies; define quality KPIs, participate in architecture reviews, and mentor engineers.

As a Senior Software Engineer, you will develop web and desktop applications, guide projects, mentor junior engineers, and ensure high-quality code delivery.

Leads and grows the engineering team responsible for Dialpad’s calling experience across frontend, backend, real-time audio, contact center capabilities, and hardware devices. Defines the team vision and roadmap, owns large-scale architectural evolution, improves reliability and performance, oversees delivery, recruits and mentors engineers, and partners cross-functionally. The role requires hands-on technical leadership in WebRTC, SIP, VoIP, cloud-native systems, AI-assisted development, and high-traffic production platforms.

Conduct R&D and implement state-of-the-art NLP and ML algorithms for real-time, agentic voice and chat systems. Build and deploy LLM-based, multilingual and multimodal features, manage large text datasets, evaluate model performance, collaborate with engineering and product teams, and publish research.

Design, develop, and maintain software integrations for VoIP devices and device management. Implement provisioning, activation, UI device controls, and REST APIs; troubleshoot production issues; write unit tests; review code; collaborate with Product, Design, QA, and cross-functional teams.

Provides independent legal counsel on AI governance, product privacy, data protection, security certifications, telecom-related compliance, commercial contracts, marketing, incident response, and regulatory obligations. Advises Product, Engineering, Security, Sales, Marketing, and Customer Success teams on GDPR, CCPA/CPRA, HIPAA, biometric privacy, AI laws, call recording, and cross-border data transfers. Supports privacy programs, data requests, breach response, legal operations, and practical compliance frameworks.

Own the full mid-market sales cycle, from lead conversion and strategic prospecting through complex deal closure. Build pipelines, develop multi-stakeholder opportunities, collaborate with SDRs, partners, sales engineers, and leadership, and manage forecasts and deal reviews. The role focuses on acquiring new customers and solving business communication challenges using Dialpad’s SaaS products.

Lead architecture and delivery of Dialpad's agentic AI platform, building scalable multi-agent orchestration, memory and retrieval systems, real-time voice reasoning, inference optimization, safety/observability, and production integrations while mentoring engineers and partnering with product and research.

Lead architecture and delivery of Dialpad's agentic AI platform: build scalable multi-agent orchestration, real-time conversational and voice reasoning, retrieval and memory systems, inference/fine-tuning pipelines, observability and safety frameworks, and mentor engineering teams while partnering cross-functionally to productionize autonomous workflow execution.

Lead platform-level product design for AI-first business communications. Define patterns, primitives, and interaction models, ship coded prototypes and production code, evolve the design system, mentor designers, and drive cross-team AI-enabled tooling and infrastructure.

Own product direction for custom SLMs, ASR, and real-time inference across the full model lifecycle: data acquisition and annotation, training and adaptation, evaluation, release, monitoring, and retirement. Define data strategy and quality bars, run evals and error analyses, make trade-offs between latency, cost, and model capability, and coordinate with product engineering and GTM while owning release and rollback decisions.