Senior Full-stack Engineer

Senior Full-stack Engineer (Voice AI)

• No equity
• Remote (Buenos Aires Province Rio de Janeiro Mexico City Remote)
• 5 years of exp
• Contract

About the job

Senior Software Engineer

Required

• 5+ years of professional software engineering experience building and maintaining production applications.
• Strong full-stack engineering experience with a clear backend emphasis. This person should be capable on the frontend, but we are primarily looking for depth in backend architecture, APIs, data, integrations, and production systems.
• Strong professional experience with JavaScript, TypeScript, Node.js, Python, particularly for backend services, automation, AI integrations, or data-intensive workflows.
• Strong experience designing, building, and integrating REST APIs, webhooks, third-party APIs, and service-to-service integrations.
• Experience building and operating production systems in AWS, including familiarity with cloud infrastructure, deployment, storage, networking, logging, monitoring, and security concepts.
• Deep PostgreSQL and relational database experience, including data modeling, schema design, migrations, indexing, query optimization, data integrity, and debugging performance issues.
• Experience designing backend systems that are reliable, maintainable, observable, and scalable, including appropriate use of queues, background jobs, caching, retries, logging, monitoring, and error handling.
• Demonstrated experience owning software through the full product development lifecycle: understanding requirements and customer problems, designing a solution, implementing it, deploying it, monitoring it, and iterating based on real-world usage.

AI and automation experience

• Strong hands-on experience building with LLMs, AI agents, and AI assistants in production.
• Ability to design agentic workflows where models can reason over context, call tools and APIs, execute multi-step tasks, maintain state, and interact reliably with external systems.
• Experience implementing the patterns required to make AI systems dependable, including tool/function calling, structured outputs, prompt and context management, orchestration, guardrails, retries, fallback behavior, observability, testing/evaluation, and failure handling.
• Ability to determine when an AI agent is appropriate versus when deterministic software or workflow automation is the better solution, and to design systems that combine both effectively.
• Experience with workflow automation and orchestration, using tools such as n8n or equivalent technologies.
• Comfortable using AI-powered engineering tools and coding agents to accelerate development, debugging, investigation, testing, documentation, and internal workflows.
• Preferred, but not required
• Experience building Voice AI, conversational AI, telephony, speech-to-text, or text-to-speech systems.
• Experience with agent frameworks, orchestration platforms, or custom agent architectures.
• Experience working with healthcare software, EHR integrations, scheduling systems, or healthcare interoperability.
• Experience in an early-stage startup or another environment where engineers have significant ownership and limited process.
• Experience mentoring other engineers or serving as a technical lead.
• Experience with n8n specifically.

The type of engineer we want

We are not looking for someone who needs fully defined tickets before beginning work. We want someone who can be given a problem rather than a specification: someone who investigates it, asks the right questions, identifies a path forward, communicates tradeoffs, builds the solution, and follows through after it reaches production.

The right person is:

• Highly self-directed and comfortable operating with limited structure.
• Product-minded and interested in why something is being built, not only how.
• Comfortable making decisions and taking ownership while knowing when to ask for input.
• Pragmatic: capable of moving quickly without creating unnecessary technical debt.
• Naturally inclined to improve systems, automate repetitive work, and remove bottlenecks.
• Comfortable moving across backend systems, APIs, databases, cloud infrastructure, automation, and AI systems as the problem requires.
• Collaborative and capable of making the engineers around them more effective.