Senior AI-Augmented Full-Stack Engineer (Node.js / Next.js)

We are seeking a product-minded senior Full-Stack Engineer who builds scalable backend services and modern web applications with AI-native development practices at the core.

In this role, you will architect AI-assisted development workflows, orchestrate coding agents, and integrate automation across the engineering pipeline — while upholding strong security standards, code consistency, and system reliability.

You will also own how those services are containerized, deployed, and operated on GCP : this role sits where the services meet the infrastructure.

This is a technical leadership role, not a ticket‑taking one.

You will set direction rather than wait for it — leading design decisions that cut across services, raising the engineering bar through review and mentorship, and defining how the team builds, ships, and operates.

We expect you to make calls with incomplete information, own the outcome, and bring the rest of the team along with you.

We also move fast.

Priorities get re-cut, scope shifts mid‑flight, and you will frequently be the one deciding what ships this week and what can wait — often without a spec handed to you.

In exchange you get real autonomy and a short path from idea to production.

Our one hard rule is that speed never comes out of reliability: you move quickly, and you still own what you shipped after it reaches production.

Responsibilities

• Core Engineering
• Design and develop RESTful APIs using Node. js — and in Go or Python where the workload calls for it
• Build responsive web applications using Next. js
• Design service boundaries in a microservice architecture and the communication between them — synchronous APIs vs. message queues — with the trade-offs made explicit
• Use Redis and message queues where they belong: caching, rate limiting, background jobs, retries, and idempotency — and know when they're the wrong tool
• Design database schemas and optimize queries across My SQL and Mongo DB
• Write clean, maintainable, and testable code with automated test coverage
• Containerize services with Docker and deploy and maintain services on Google Cloud Platform with CI/CD pipelines — including environment and secrets configuration, rollout, and rollback
• Set up the observability that makes incidents diagnosable: logging, metrics, tracing, and alerting that fires on the right things
• Identify performance bottlenecks and propose scalable, well-architected solutions — from query plans to container limits
• Own a domain end-to-end: design, build, ship, and operate it after launch
• AI-Driven Development
• Set up and manage AI coding agents as part of daily development workflow, including configuring project context, rules, and memory for consistent output
• Build and maintain AI-powered sub-agents and automated bots that accelerate team-wide delivery — such as PR reviewers, test generators, and documentation assistants
• Design multi-tool AI stacks where different agents handle distinct phases of the development lifecycle, from research and architecture through coding, review, and deployment
• Automate repetitive engineering and operational tasks using workflow automation platforms or custom scripting
• Evaluate and adopt emerging AI development tools, keeping the team ahead of industry evolution
• Help establish and maintain security practices and review protocols for AI-generated code, including dependency auditing, secrets management, and output validation
• Collaboration & Standards
• Conduct code reviews incorporating both human judgment and AI-assisted review workflows
• Write technical design docs and lead decisions that cut across services
• Mentor 1–2 engineers and raise the bar on the team's code review standard
• Share ownership of production reliability — incident response and postmortems
• Document AI tooling configurations to enable team-wide adoption and consistency
• Continuously raise engineering standards by embedding AI capabilities into the software development lifecycle
• Nice‑to‑Have
• Deeper Flutter / Dart experience — we have a mobile app in production
• Familiarity with Firebase, or with Infrastructure as Code (Terraform / Pulumi)
• Observability and cost optimization on GCP — or having scaled something past its first painful limit
• Experience building MCP servers, custom tool integrations, or AI-driven automation workflows
• Background in tech startups or fast-paced product environments
• Interest in mental health or health technology
• Tools & Environment
• Engineering: Git Hub, Jira, Discord, Notion, Google Cloud Platform, Docker, Redis
• AI Development Stack: Claude Code, Cursor / Windsurf, Kimi, Git Hub Copilot, n8n, MCP Integrations
• Health Insurance
• Hybrid Work
• Annual Leave 12 days
• Mental Health counseling sessions with psychiatrists and psychologists through ooca platform
• Social Security Insurance
• Provident Fund (condition applied)
• Special discount home loan interest with Government Housing Bank
• BYOD policy: Personal laptops less than 3 years old are eligible for 1000 THB/month subsidy (registration required)
• Mandatory Qualifications & Requirements
• At least 5 years of experience in Software Development
• Proven experience in Node. js backend development
• Experience building web applications with Next. js or equivalent modern React frameworks
• Strong understanding of API design, relational and non-relational databases, and system architecture
• Proficiency with Git, CI/CD pipelines (Git Hub Actions), Docker, and modern development collaboration tools
• Hands‑on experience deploying and operating services on Google Cloud Platform — strong with infrastructure and deployment, not just writing application code
• Experience designing and running microservices, including caching and asynchronous processing with Redis and message queues
• Working knowledge of at least one additional backend language among Go, Python, or Dart.

We don't expect depth in all of them — deep in Node. js and quick to pick up the rest is what matters

• Hands‑on experience with AI coding tools such as Claude Code, Cursor, Git Hub Copilot, Windsurf, Kimi, or Cline — with demonstrated ability to integrate them into production development workflows
• Ability to configure and orchestrate AI agents, including setting up project rules, context files, sub-agents, and skill definitions to produce consistent, production‑grade output
• Security-conscious approach to AI-assisted development, with awareness of risks such as unverified dependencies, credential exposure, and inconsistent code patterns
• Proactive mindset toward the evolving AI tooling landscape, with a track record of adopting and adapting new tools
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