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