Senior Software Engineer

Recruiting From Scratch•San Francisco, CA

10h•$130,000 - $190,000•Remote

About The Position

The Senior Software Engineer builds and ships full-stack features for AI-powered voice and chat products. The role owns projects from problem definition through implementation, testing, deployment, and iteration, working with technologies including TypeScript, React, Node.js, and Python. Engineers integrate LLM capabilities into production workflows, including prompt engineering, multi-turn agents, tool use, and conversational AI patterns, and collaborate with product and machine learning teams to turn model capabilities into practical features. The position also improves voice and conversational systems, including speech recognition and text-to-speech capabilities. It addresses conversation quality, latency, reliability, and operating costs, and contributes to systems supporting millions of enterprise customer interactions. Engineers maintain large-scale production software, resolve complex issues, improve performance and scalability, and balance cost, latency, reliability, and user experience. The role collaborates across engineering, product, and machine learning teams and may contribute to core product or forward-deployed engineering initiatives. It involves translating customer requirements into technical solutions, bringing deployment insights back to the product, contributing to system design and engineering standards, and taking broad ownership in a lean, fast-moving organization. The position is fully remote within the United States or Canada, with company and team gatherings approximately every six weeks. The base salary is $130,000–$190,000, with competitive equity.

Requirements

5–8 years of experience as a full-stack software engineer.
Demonstrated experience operating at a senior software engineering level.
Strong proficiency in Python or TypeScript; at least one is required.
Experience building full-stack applications, APIs, backend services, user-facing features, and production software systems.
Hands-on experience building products or features that use LLMs, with practical applied experience rather than theoretical familiarity alone.
Experience owning and shipping software that scales to millions of users or supports substantial, high-volume production workloads.
Experience taking software from design or concept through deployment and ongoing improvement.
Experience in a startup, high-growth technology company, or similarly fast-moving engineering environment.
Ability to diagnose production issues and understand performance, reliability, scalability, and system design.
Ability to work independently, take ownership of ambiguous projects, manage multiple initiatives, and adapt to changing priorities.
Ability to work across the stack, make sound technical decisions, and deliver maintainable software.
Ability to explain how LLMs are used in a real product or production workflow and address reliability, latency, response quality, and cost.
Strong initiative, curiosity, adaptability, and willingness to learn; ability to reflect on feedback and mistakes and apply those lessons.
Ability to collaborate with engineering, product, and machine learning teams and communicate technical decisions and trade-offs clearly.
Ability to give and receive code review feedback constructively and take accountability for results.
Must have valid work authorization in the United States or Canada; new visa sponsorship and visa transfers are not supported.

Nice To Haves

Conversational AI, voice AI, or multi-turn agent experience.
Experience at a company specializing in conversational AI, voice AI, or enterprise contact-center technology.
Experience at Poly, Decagon, Sierra, Five9, Genesys, ElevenLabs, NICE, Talkdesk, or RingCentral.
Experience with multi-turn conversational agents or LangChain.
Experience integrating speech recognition and text-to-speech technologies.
Experience with Rust.
Familiarity with Google Cloud Services and Kubernetes.
Experience with MySQL, PostgreSQL, and cloud infrastructure.
Experience improving CI/CD pipelines and production deployment workflows.
Experience in forward-deployed engineering or working directly on customer-specific technical challenges.
Experience building AI products used by enterprise customers.
Familiarity with React and Node.js, particularly for candidates with a TypeScript background.
Familiarity with relational databases such as MySQL or PostgreSQL and cloud platforms such as AWS, Google Cloud, or Azure.

Responsibilities

Design, develop, test, deploy, and iterate on full-stack features for AI-powered voice and chat products.
Integrate LLM capabilities into production systems and customer-facing workflows, using prompt engineering, multi-turn agents, tool use, and conversational AI patterns.
Improve speech recognition, text-to-speech, and conversational AI capabilities, including conversation quality, latency, reliability, and cost.
Build and maintain software for large-scale enterprise production workloads; identify bottlenecks and improve performance, reliability, and scalability.
Investigate production issues and implement durable solutions.
Collaborate with Engineering Managers, Product, Machine Learning, and engineers across teams to prioritize and deliver product capabilities.
Contribute to core product development or forward-deployed engineering initiatives as needed.
Translate customer requirements into technical solutions, address implementation challenges, and bring deployment insights back into the core product.
Write maintainable, testable, production-ready code; participate in code reviews and contribute to engineering standards.
Contribute to system design, technical decisions, architecture, cloud infrastructure, databases, deployment workflows, and CI/CD pipelines.
Independently drive projects, manage multiple initiatives, adapt to changing priorities, and contribute to a culture of accountability and technical ownership.