Note: The job is a remote job and is open to candidates in USA. Recruiting from Scratch is recruiting for an unnamed company that builds AI-powered voice and conversational agents for enterprises. The Senior Software Engineer will build and ship full-stack and LLM-powered products, improve voice and conversational AI systems, and own scalable production systems while collaborating across engineering, product, and machine learning teams.
Responsibilities
- Design, develop, and ship full-stack features across AI-powered voice and chat products
- Build user-facing and backend capabilities that improve the functionality, reliability, and scalability of the platform
- Work with TypeScript, React, Node.js, Python, and related technologies
- Own engineering projects from initial problem definition through implementation, testing, deployment, and iteration
- Contribute to product capabilities that help meet customer needs and support business growth
- Build and improve products powered by large language models
- Integrate LLM capabilities into production systems and customer-facing workflows
- Work with prompt engineering, multi-turn agents, tool use, and conversational AI patterns
- Experiment with new approaches to improve the quality, reliability, and effectiveness of AI-driven interactions
- Collaborate with product and machine learning teams to turn model capabilities into practical product features
- Help integrate and improve speech recognition, text-to-speech, and conversational AI capabilities
- Build systems that support natural, reliable, multi-turn conversations
- Investigate challenges related to conversation quality, response latency, system reliability, and operating costs
- Debug production issues and improve the performance of AI-powered voice and chat experiences
- Contribute to technology that supports millions of customer interactions for enterprise clients
- Build and maintain software designed to support large-scale, enterprise production workloads
- Identify bottlenecks and improve system performance, reliability, and scalability
- Balance latency, cost, reliability, and user experience when making technical decisions
- Investigate complex production issues and implement durable solutions
- Apply sound engineering judgment when evolving systems that are already used by enterprise customers
- Work with engineers across multiple product teams to deliver important product capabilities
- Partner with Engineering Managers, Product, and Machine Learning teams to prioritize and execute projects
- Contribute to core product development or forward-deployed engineering initiatives, depending on team needs
- Share technical knowledge, review code, and contribute to engineering standards
- Take ownership of multiple initiatives in a lean organization where engineers have broad responsibilities
- Work on customer-driven engineering projects when needed
- Translate real-world customer requirements into practical technical solutions
- Build or adapt product capabilities to address complex customer use cases
- Collaborate with customer-facing and internal teams to resolve implementation challenges
- Bring insights from customer deployments back into the core product
- Write maintainable, testable, and production-ready code
- Participate in code reviews and help maintain high engineering standards
- Contribute to system design, technical decision-making, and architectural improvements
- Work with cloud infrastructure, databases, deployment workflows, and CI/CD pipelines
- Identify opportunities to simplify systems and improve engineering efficiency
- Independently drive projects and make progress without requiring constant direction
- Move between product development, debugging, system design, and cross-functional collaboration as needed
- Learn unfamiliar technologies and domains quickly
- Reflect on feedback, identify areas for improvement, and continuously develop engineering skills
- Contribute to a culture of initiative, accountability, and broad technical ownership
Skills
- Must have valid work authorization in the United States or Canada. New visa sponsorship and visa transfers are not supported
- 5–8 years of experience as a full-stack software engineer
- Demonstrated experience operating at a senior software engineering level
- Experience owning and shipping software solutions that scale to millions of users or support substantial production workloads
- Hands-on experience building products or features that use LLMs
- Experience working in a startup, high-growth technology company, or similarly fast-moving engineering environment
- Strong ownership of projects from design through deployment and ongoing improvement
- Ability to work independently, manage multiple initiatives, and adapt to changing priorities
- Strong proficiency in **Python or TypeScript**; at least one is required
- Experience with full-stack application development and production software systems
- Experience building APIs, backend services, and user-facing product features
- Ability to make sound technical decisions and deliver maintainable software
- Experience taking features from concept to production rather than working exclusively on isolated components
- Hands-on experience building or integrating LLM-powered products
- Familiarity with prompt engineering, multi-turn agents, or LLM orchestration tools such as LangChain
- Ability to explain how LLMs are used in a real product or production workflow
- Experience addressing practical challenges such as reliability, latency, response quality, and cost
- Candidates should demonstrate applied experience rather than theoretical familiarity with LLMs alone
- Experience owning and shipping software that serves millions of users or supports high-volume production workloads
- Ability to diagnose and resolve production issues
- Understanding of performance, reliability, scalability, and system design
- Familiarity with relational databases such as MySQL or PostgreSQL
- Experience with cloud platforms such as AWS, Google Cloud, or Azure
- Familiarity with CI/CD pipelines and modern deployment practices
- Ability to balance engineering quality with the need to ship useful product improvements quickly
- Strong initiative and a proactive approach to engineering challenges
- Comfortable taking ownership of ambiguous projects and driving them to completion
- Able to work across the stack and contribute outside a narrowly defined specialty
- Uses sound judgment when choosing between different technical approaches
- Demonstrates curiosity, adaptability, and a willingness to learn
- Can reflect on mistakes and feedback and apply those lessons to future work
- Works effectively with engineering, product, and machine learning teams
- Communicates technical decisions and trade-offs clearly
- Gives and receives code review feedback constructively
- Demonstrates self-awareness and a willingness to improve
- Takes accountability for results rather than focusing only on assigned tasks
- Comfortable in a lean organization where engineers own multiple initiatives
- Conversational AI, voice AI, or multi-turn agent experience is a strong advantage
- Experience at companies 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 a forward-deployed engineering role or working directly on customer-specific technical challenges
- Experience building AI products used by enterprise customers
Benefits
- Competitive equity with potential long-term upside.
- Fully remote work within the United States or Canada.
- Company and team gatherings approximately every six weeks.
- 100% coverage of medical, dental, and vision insurance.
- Flexible vacation policy.
- Technology and learning stipend.
- Paid sabbatical after five years.
- Opportunity to work on production AI agents serving Fortune 500 companies.
- Significant engineering ownership in a lean organization.
- Opportunity to work with modern LLMs, conversational AI, and voice AI technologies.
Company Overview