[Remote 2jobs] Fullstack Engineer (System design, AI Native, Nodejs) _ English good

REMOTE - Fullstack Developer – TypeScript/ System design / AI-Native
Type of work: Remote 13h00 ~ 22h00
Range: up to 4k
Contract: 3 months (extend Labol contract 12 months
Interview process: 1 round HR + 1 Round AI test + 2 round technical với client
English: C1 /C2
Contact: Nhung 0964 285 657 / nhungnguyen137.hr@gmail.com
About this role
We are looking for a highly technical, hands-on Fullstack Developer who is comfortable going deep into complex systems, solving ambiguous problems, and owning technical outcomes end-to-end.
This is a hardcore engineering role. We are looking for someone who can independently investigate problems, make sound technical decisions, challenge assumptions, and take full responsibility for the quality and reliability of what they ship.
You will work extensively with TypeScript, React, Node.js/NestJS, distributed systems, event-driven architecture, real-time communication, and AI-assisted engineering workflows.
AI is an important part of how we work, but AI does not replace engineering judgment. You should be able to use AI aggressively to increase your productivity while still understanding, reviewing, testing, challenging, and taking ownership of the final solution.
Requirements
What You'll Do
End-to-End Technical Ownership
Own features and technical problems from requirement clarification through production.
Understand requirements deeply before implementation; identify ambiguity, edge cases, dependencies, and technical risks.
Design, implement, test, deploy, monitor, and troubleshoot end-to-end features.
Take responsibility for production quality, reliability, performance, and maintainability.
Investigate unfamiliar systems and technical problems independently rather than waiting for detailed instructions.
Drive problems to resolution, including coordinating with other engineers when dependencies or cross-service issues are involved.
Hardcore Engineering
Build and evolve scalable services, APIs, and system architecture.
Design robust backend solutions involving concurrency, distributed systems, event-driven architecture, and real-time communication.
Work hands-on across the stack, with strong emphasis on backend engineering.
Investigate complex production issues using logs, metrics, traces, monitoring, debugging, and other observability tools.
Identify root causes rather than treating symptoms.
Make pragmatic engineering decisions balancing speed, maintainability, scalability, performance, reliability, and technical debt.
Improve engineering practices, tooling, automation, testing, and development workflows.
Communication & Engineering Agency
Proactively communicate technical decisions, progress, blockers, risks, and dependencies.
Ask clarifying questions when requirements are unclear instead of making assumptions and proceeding blindly.
Challenge unclear or technically risky requirements when necessary.
Collaborate closely with Product, Design, Engineering, and international stakeholders.
Work effectively in a distributed/remote environment with a high degree of independence.
Keep stakeholders informed without requiring constant follow-up.
Explain complex technical concepts clearly to both technical and non-technical audiences.
AI-Native Engineering
Use AI tools and coding agents extensively throughout the engineering lifecycle: coding, architecture, debugging, investigation, testing, documentation, and code review.
Break down complex problems into well-scoped tasks that can be delegated to AI agents.
Manage multiple AI-assisted tasks or agents in parallel while preserving requirements, context, dependencies, and technical direction.
Maintain persistent context using structured documentation, project instructions, CLAUDE.md-style files, or equivalent approaches.
Review, test, challenge, and validate AI-generated code and recommendations before accepting or shipping them.
Detect incorrect assumptions, hallucinations, incomplete implementations, regressions, security issues, and edge cases in AI-generated output.
Know when to delegate to AI and when a problem requires direct engineering investigation and reasoning.
Continuously improve how AI is integrated into engineering workflows.
What We're Looking For
1. Technical Excellence
8+ years of professional software engineering experience.
Deep hands-on experience with: TypeScript, React, Node.js / NestJS, REST APIs
Strong backend engineering capability is critical for this role.
Candidates should have a strong backend skill level, ideally 4–5/5 in their own assessment.
Strong understanding of: API design, Distributed systems, Concurrency, Scalability, Performance optimization, Reliability, System design
Solid experience with event-driven architecture and messaging systems, particularly Kafka.
Strong experience with NoSQL databases and production database engineering, particularly MongoDB, including:Data modeling, Indexing, Query optimization, Replica sets, Sharding, Production troubleshooting
Hands-on experience building and operating high-concurrency / real-time systems, including: WebSockets, Socket.IO, Horizontal scaling, Real-time event processing
Experience with WebRTC, MediaStream, browser APIs, and audio/video technologies is highly valuable.
2. Ownership & Engineering Agency
We are looking for an engineer who:
Can work independently with minimal supervision.
Takes ownership of outcomes, not just assigned tasks.
Proactively investigates problems and proposes solutions.
Asks questions and clarifies requirements when something does not make sense.
Raises risks and blockers early.
Is comfortable making technical decisions under ambiguity.
Takes responsibility for bugs, regressions, and production issues.
Can explain why a technical decision was made and what trade-offs were considered.
Does not stop at "the code works" — they verify whether the solution actually solves the underlying problem.
Strong agency is a must-have for this role.
3. AI-Native Engineering
Extensive hands-on experience using AI coding assistants and/or AI agents in day-to-day engineering work.
Ability to orchestrate multiple AI-assisted tasks while maintaining technical context.
Experience creating or maintaining persistent AI context/instructions for projects.
Strong ability to decompose complex technical problems into AI-delegatable tasks.
Strong engineering judgment when evaluating AI-generated solutions.
Ability to independently verify AI output through: Code review, Testing, Debugging, Documentation, Observability, Source-code investigation, Production validation
Understands the limitations of AI and knows when not to trust or delegate to AI.
4. Communication & Collaboration
Excellent English communication skills — C1 level / IELTS 7.0+ equivalent.
Comfortable communicating directly with international teams and stakeholders.
Able to clearly explain technical problems, decisions, trade-offs, and risks.
Proactive in asking questions and seeking clarification.
Comfortable challenging assumptions respectfully.
Experience working effectively in remote or distributed engineering teams.
Strong asynchronous communication and documentation habits.
5. Engineering Mindset
Strong computer science fundamentals or equivalent practical engineering experience.
High attention to correctness, quality, and production reliability.
Strong debugging and problem-solving ability.
Curious and comfortable diving into unfamiliar codebases and systems.
Pragmatic mindset: able to move quickly without sacrificing eng

Work arrangement
Yes