# Software Engineer

**Company:** [Dialpad](https://hotfix.jobs/companies/dialpad)
**Location:** San Francisco, CA
**Role:** ML Engineering
**Salary:** $176k – $209k/yr
**Experience:** 10+ years
**Skills:** Distributed Systems, llm platforms, agentic architectures, LangChain, LangGraph, crewai, inference optimization, retrieval systems, memory architectures, Evaluation Frameworks, Observability, streaming infrastructure, voice ai, api tool integration, human-in-the-loop systems
**Posted:** 2026-07-29

> Lead the architecture and development of Dialpad's autonomous Agentic AI platform, building multi-agent orchestration, memory systems, real-time reasoning, and tool execution for enterprise workflows. Requires 10+ years experience, technical leadership at Staff/Principal level, and deep expertise in LLM platforms, agent frameworks, and production AI infrastructure.

## Job Description

## What you’ll do

- Drive Technical Strategy: Own the architectural roadmap and delivery of Dialpad’s Agentic infrastructure, core orchestration layers, memory architectures, and evaluation/observability systems.
- Build & Scale: Design and deploy scalable, multi-modal AI agents capable of autonomous support, real-time voice reasoning, and secure API tool execution across complex enterprise workflows.
- Mentor & Influence: Act as a technical anchor for the organization, raising the engineering bar, mentoring senior peers, and defining technical standards for an AI-native SDLC.
- Partner Cross-Functionally: Collaborate with leadership across Product, Engineering, and Applied Research to align technical execution with Dialpad’s long-term business strategy.
- Push the Frontier: Research and implement emerging agent frameworks, LLM inference optimization, advanced retrieval systems, and cutting-edge safety/policy guardrails to keep Dialpad at the absolute forefront of the "era of the agent."

## Skills you’ll bring

- 10+ years of relevant software engineering experience, with a proven track record of technical leadership (as a Staff, Senior Staff, or Principal Engineer) shipping complex, large-scale systems.
- Strong foundations in scaling distributed systems and production-grade infrastructure before evolving into applied AI, LLM platforms, and agentic architectures.
- Ability to lead and grow a small group of engineers.
- Inference optimization and fine-tuning strategies.
- Advanced retrieval systems and memory architectures.
- Hands-on experience with frameworks like LangChain/LangGraph, CrewAI, or AWS/Google Agent ecosystems.
- Evaluation, observability, and safety frameworks for production AI systems.
- Streaming infrastructure and voice/conversational AI.
- Tool use, API execution frameworks, and human-in-the-loop validation systems.
- Experience setting clear technical goals, identifying architectural risks, and systematically clearing tech-debt gaps.
- Ability to thrive in ambiguity, build cutting-edge AI products from the ground up, and scale them into robust, self-sustaining enterprise systems.

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