Senior Software Engineer

Koveret is seeking a Senior Software Engineer with expertise in AI/ML and full-stack development to join their remote team. This role requires a minimum of three years and up to eight years of professional software engineering experience. The ideal candidate will be a hands-on engineer capable of owning complex projects across Koveret’s PHP/Laravel SaaS platform, modern web applications, AI-driven features, and cloud infrastructure. You will be responsible for taking problems from concept to production, including design, development, deployment, and ongoing maintenance. Comfort with modern AI tools and strong engineering judgment are essential, as is the ability to collaborate effectively during New York business hours (Eastern Time).

Key Responsibilities

- Own the full lifecycle of features, from technical design through development, testing, deployment, and production support.
- Develop and enhance applications, APIs, background jobs, and integrations primarily using PHP and Laravel.
- Architect scalable, secure, and maintainable solutions for a multi-tenant SaaS platform, focusing on data integrity and performance.
- Work across the technology stack with React, Next.js, Node.js, Python, and Django as needed.
- Design and implement AI agents and agentic workflows capable of using tools, accessing data, and completing tasks with appropriate controls and monitoring.
- Build AI features leveraging LLM APIs, retrieval-augmented generation (RAG), LangChain, and LangGraph.
- Utilize Model Context Protocol (MCP) tools and servers to integrate AI assistants with applications, data sources, and development workflows.
- Employ AI development tools such as Claude for research, debugging, automation, and validating AI-generated outputs before production deployment.
- Craft effective AI prompts and critically evaluate AI outputs for accuracy, reliability, and practical application.
- Design RESTful APIs and integrate third-party services to extend platform capabilities.
- Optimize database queries, application performance, logging, monitoring, and incident response processes.
- Build and maintain CI/CD pipelines, automated testing, and reliable deployment workflows.
- Configure and manage cloud infrastructure on Google Cloud and/or AWS using best DevOps practices.
- Conduct code reviews, troubleshoot complex issues, and contribute to raising engineering standards across the team.
- Communicate progress, risks, and technical decisions clearly while collaborating during Eastern Time business hours.

Required Qualifications

- Bachelor’s degree in Computer Science, Software Engineering, or a related discipline.
- Minimum of 3 years of professional software engineering experience; candidates with 3 to 8 years are encouraged to apply.
- Strong, hands-on experience with PHP and Laravel frameworks.
- Proven track record building and maintaining production-grade applications, APIs, and databases.
- Practical experience with AI development tools and large language model (LLM) APIs, including AI agents, Claude, MCP, RAG, LangChain, or LangGraph.
- Experience with DevOps practices, CI/CD pipelines, cloud deployments, and production troubleshooting.
- Solid understanding of system architecture and ability to make sound technical decisions independently.
- Working knowledge of React, Next.js, Node.js, Python/Django, automation, and cloud platforms such as Google Cloud or AWS.
- Ability to write clear AI prompts, evaluate AI-generated content critically, and solve problems autonomously.
- Strong ownership mentality, professional work habits, and excellent communication skills. Ability to work independently and escalate blockers appropriately.
- Availability to collaborate during New York business hours (Eastern Time).

Koveret values engineers who stay current with emerging technologies, think creatively, solve problems independently, and take full responsibility for the quality of their work. This position is intended for experienced professionals; candidates with less than three years of professional experience will not be considered.

Applicants are encouraged to apply directly through the job posting and provide a brief description of projects they have built or maintained, including examples of AI agents, workflows, or integrations they have implemented.