Senior AI & Full-Stack Engineer - DevOps & Technical Leadership

Location: 100% Remote Employment: Full-time, long-term position Start date: As soon as possible after selection and agreement Salary: Startup-aligned starting compensation, based on experience and responsibilities, with

Location: 100% Remote

• Employment: Full-time, long-term position
• Start date: As soon as possible after selection and agreement
• Salary: Startup-aligned starting compensation, based on experience and responsibilities, with the potential for substantial growth during the first few years
• About UsWe are a startup developing software products, web applications, AI-powered tools, integrations, and business automations across different projects.
• Our delivery model combines internal ownership with outsourced development. We work with external developers and specialists, and we need strong technical leadership to turn their contributions into reliable, maintainable software.
• AI-assisted and agentic development are central to how we work. We want to move quickly, make sensible technical decisions, and build solutions that our team can understand, operate, and improve.
• We are looking for an experienced engineer who wants to join at an early stage, take meaningful responsibility, and grow with the company.
• Job DescriptionWe are seeking a Senior AI & Full-Stack Engineer who can develop applications across frontend and backend, integrate AI capabilities, and manage the Linux infrastructure, databases, and deployment processes supporting them.
• You should be comfortable taking a project from an initial business requirement through implementation, testing, deployment, and ongoing operation. You will work across different products and internal initiatives, helping us choose practical solutions and deliver them efficiently.
• Alongside hands-on engineering, your responsibilities may include leading developers, mentoring less experienced colleagues, coordinating outsourced contributors, and reviewing externally delivered work. Previous team leadership and mentoring experience are therefore important.
• This is an opportunity to help establish the engineering foundations of a growing startup and develop into a broader technical leadership position.
• Key Responsibilities
• Develop and maintain web applications across frontend and backend.
• Build AI-powered features, integrations, internal tools, and business automations.
• Use AI coding assistants and coding agents effectively, with appropriate testing and human review.
• Translate business requirements into clear implementation tasks and verifiable acceptance criteria.
• Design APIs, business logic, authentication, authorization, and third-party integrations.
• Manage database schemas, migrations, query performance, backups, and recovery procedures.
• Administer Linux servers, including application services, permissions, updates, networking, and troubleshooting.
• Build and maintain Docker environments, including container networking, persistent storage, configuration, and health checks.
• Manage DNS records, domain routing, TLS certificates, and reverse proxies.
• Maintain CI/CD workflows using GitHub Actions, Azure DevOps Pipelines, and appropriate build agents or runners.
• Carry out deployments with migration checks, rollback procedures, and post-deployment verification.
• Investigate production incidents and address their underlying causes.
• Coordinate outsourced developers and specialists, clarify requirements, review deliverables, and manage technical dependencies.
• Mentor developers through code reviews, practical demonstrations, and constructive feedback.
• Keep implementation proportionate to the problem, controlling unnecessary complexity, infrastructure costs, and maintenance overhead.
• Required Qualifications
• Demonstrated senior-level experience delivering and maintaining production web applications.
• Strong frontend development skills using a modern framework, JavaScript or TypeScript, HTML, and CSS.
• Strong backend development experience, including secure APIs, integrations, validation, and error handling.
• Practical experience integrating AI or LLM capabilities into software, including checking output quality, handling failures, and managing latency and usage costs.