AI-Powered Principal Fullstack Engineer Java/Go/RoR
Hạn nộp hồ sơ: 18/09/2026 (Còn 8 ngày)
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Mô tả công việc
Tóm tắt công việc
An implementer who takes direction from product and domain experts, uses generative AI (LLMs), no-code/low-code, and hands-on engineering to move from "what to build" to working prototypes and initial implementations in days -not weeks. This role bridges product, UX, and engineering: you shape the "how" at maximum speed, then hand off testable, specified work to the broader engineering organization.
This role expects a strong security mindset, with a clear understanding of data privacy, credential protection, device security, and the responsible use of corporate systems, tools, and accounts.
Responsibilities
Work from business requirements and constraints set with domain experts; design prompts and AI-assisted workflows and translate needs into clear system and UX specifications.
Rapid prototyping (UI/UX mockups, thin vertical slices, foundational implementations) using AI tools, no-code/low-code, and code where it accelerates outcome.
Run hypothesis validation cycles on prototypes; deliver high-fidelity handovers (behaviour, data contracts, non-functional notes) to engineering teams.
Decode legacy specifications and extend existing products using AI-assisted analysis and implementation where appropriate.
Continuously evolve how the product team builds-tooling, templates, and practices-as models and platforms change.
Financial Benefits:
Attractive Salary Package
Insurance based on full salary (Social Insurance, Health Insurance, Unemployment Insurance)
Private health insurance and accident insurance for employees. Covering for family member, applied from manager level
Full salary during probation period
17 paid leaves per year
Working environment:
Very well-equipped facility: Macbook, Additional monitor
Hybrid working model with 2 working days in office per week
Annual Company trip and Quarterly Team building
Working in an international environment with nice and supportive colleagues
Work life balance environment
Sport clubs in the company for engagement activities: billiard club, running club
Career Development:
Clear Career path
External & internal training courses
Soft-skill workshops
Monthly and biannual Recognition Awards
Performance & salary review: twice/year (Jun & Dec)
An implementer who takes direction from product and domain experts, uses generative AI (LLMs), no-code/low-code, and hands-on engineering to move from "what to build" to working prototypes and initial implementations in days -not weeks. This role bridges product, UX, and engineering: you shape the "how" at maximum speed, then hand off testable, specified work to the broader engineering organization.
This role expects a strong security mindset, with a clear understanding of data privacy, credential protection, device security, and the responsible use of corporate systems, tools, and accounts.
Responsibilities
Work from business requirements and constraints set with domain experts; design prompts and AI-assisted workflows and translate needs into clear system and UX specifications.
Rapid prototyping (UI/UX mockups, thin vertical slices, foundational implementations) using AI tools, no-code/low-code, and code where it accelerates outcome.
Run hypothesis validation cycles on prototypes; deliver high-fidelity handovers (behaviour, data contracts, non-functional notes) to engineering teams.
Decode legacy specifications and extend existing products using AI-assisted analysis and implementation where appropriate.
Continuously evolve how the product team builds-tooling, templates, and practices-as models and platforms change.
Financial Benefits:
Attractive Salary Package
Insurance based on full salary (Social Insurance, Health Insurance, Unemployment Insurance)
Private health insurance and accident insurance for employees. Covering for family member, applied from manager level
Full salary during probation period
17 paid leaves per year
Working environment:
Very well-equipped facility: Macbook, Additional monitor
Hybrid working model with 2 working days in office per week
Annual Company trip and Quarterly Team building
Working in an international environment with nice and supportive colleagues
Work life balance environment
Sport clubs in the company for engagement activities: billiard club, running club
Career Development:
Clear Career path
External & internal training courses
Soft-skill workshops
Monthly and biannual Recognition Awards
Performance & salary review: twice/year (Jun & Dec)
Yêu cầu
1. Full-stack engineering depth (required)
You are not only a prompt author: you ship full-stack software and can own thin slices end-to-end when the prototype must be real.
End-to-end feature development: backend services and SPAs; comfort moving across the stack for prototypes and v1 implementations.
Backend: strong hands-on skills in Java or Golang or Ruby on Rails; RESTful APIs; sound approach to microservices and backward compatibility where relevant; performance, concurrency, and clean structure in code.
Frontend: solid experience with modern frameworks such as [protected info], [protected info], [protected info], [protected info], or [protected info]; strong JavaScript, TypeScript, HTML, and CSS; awareness of testing (e.g. Jest/Mocha) and quality (linting, reviews).
Data: strong SQL skills and query tuning; ACID-aware design for transactional behaviour in prototypes.
Delivery: CI/CD (e.g. GitHub Actions, CircleCI, or similar), Git workflows, code review habits; AWS and Docker for deployable prototypes; Kubernetes exposure is a plus.
Reliability and security in scope of the prototype: authentication/authorization patterns, JWT/OAuth2 at a level appropriate to demos and handover notes; SLO/SLI thinking and observability hooks where the prototype will graduate.
Leadership of craft: contribute to architecture for your domain verticals; mentor others; incident mindset (when things break, fix and document).
2. Required experience and skills (must have)
Minimum 8 years of experience in related roles: Fullstack Developer, AI Engineer, Backend Engineer, Architecture
Generative AI: Enthusiastic, daily use of generative AI and advanced AI tooling to streamline work and materially accelerate delivery, combined with deep practical understanding of LLMs and proven application in product or internal delivery (not toy prompts only).
Product mindset: Proven track record translating high-level product requirements into detailed requirements and comprehensive technical requirements through close partnership with Product Managers and domain stakeholders.
Communication: Strong verbal and written English for clarity and alignment in distributed, multinational product engineering teams.
Prototyping and product iteration using AI tools and no-code/low-code, grounded in user and operational workflow understanding.
Comfort with ambiguity: ship "something that works first," then refine in tight loops (agile execution).
Track record as a central technical contributor on product initiatives that reached users and business outcomes.
Agile familiarity (Scrum/Kanban); strong problem-solving across technical and product uncertainty.
3. Preferred (nice to have)
Micro-frontends, state machines, advanced Java or Golang or Ruby on Rails concurrency.
Kubernetes, Kafka/RabbitMQ, Prometheus/Grafana/ELK or similar.
DDD, Clean/Hexagonal architecture; experience in accounting, finance, or other domain-heavy B2B products.
Open-source or strong continuous learning profile.
You are not only a prompt author: you ship full-stack software and can own thin slices end-to-end when the prototype must be real.
End-to-end feature development: backend services and SPAs; comfort moving across the stack for prototypes and v1 implementations.
Backend: strong hands-on skills in Java or Golang or Ruby on Rails; RESTful APIs; sound approach to microservices and backward compatibility where relevant; performance, concurrency, and clean structure in code.
Frontend: solid experience with modern frameworks such as [protected info], [protected info], [protected info], [protected info], or [protected info]; strong JavaScript, TypeScript, HTML, and CSS; awareness of testing (e.g. Jest/Mocha) and quality (linting, reviews).
Data: strong SQL skills and query tuning; ACID-aware design for transactional behaviour in prototypes.
Delivery: CI/CD (e.g. GitHub Actions, CircleCI, or similar), Git workflows, code review habits; AWS and Docker for deployable prototypes; Kubernetes exposure is a plus.
Reliability and security in scope of the prototype: authentication/authorization patterns, JWT/OAuth2 at a level appropriate to demos and handover notes; SLO/SLI thinking and observability hooks where the prototype will graduate.
Leadership of craft: contribute to architecture for your domain verticals; mentor others; incident mindset (when things break, fix and document).
2. Required experience and skills (must have)
Minimum 8 years of experience in related roles: Fullstack Developer, AI Engineer, Backend Engineer, Architecture
Generative AI: Enthusiastic, daily use of generative AI and advanced AI tooling to streamline work and materially accelerate delivery, combined with deep practical understanding of LLMs and proven application in product or internal delivery (not toy prompts only).
Product mindset: Proven track record translating high-level product requirements into detailed requirements and comprehensive technical requirements through close partnership with Product Managers and domain stakeholders.
Communication: Strong verbal and written English for clarity and alignment in distributed, multinational product engineering teams.
Prototyping and product iteration using AI tools and no-code/low-code, grounded in user and operational workflow understanding.
Comfort with ambiguity: ship "something that works first," then refine in tight loops (agile execution).
Track record as a central technical contributor on product initiatives that reached users and business outcomes.
Agile familiarity (Scrum/Kanban); strong problem-solving across technical and product uncertainty.
3. Preferred (nice to have)
Micro-frontends, state machines, advanced Java or Golang or Ruby on Rails concurrency.
Kubernetes, Kafka/RabbitMQ, Prometheus/Grafana/ELK or similar.
DDD, Clean/Hexagonal architecture; experience in accounting, finance, or other domain-heavy B2B products.
Open-source or strong continuous learning profile.
Thông tin khác
Java
Golang
Ruby on Rails
JavaScript
HTML
CSS
Machine Learning
Git
AI (Artificial Intelligence)
Prototype
MS SQL
AngularJS
TypeScript
RabbitMQ
Elasticsearch
Docker
Architecture
Observability
Grafana
DDD
Apache Kafka
Mocha
AWS
VueJS
ReactJS
Kubernetes
JWT
Microservices
RESTful API
CircleCI
Jest
NuxtJS
ACID
CI/CD
GitHub Actions
OAUTH2
LLM
Prometheus
ELK
Golang
Ruby on Rails
JavaScript
HTML
CSS
Machine Learning
Git
AI (Artificial Intelligence)
Prototype
MS SQL
AngularJS
TypeScript
RabbitMQ
Elasticsearch
Docker
Architecture
Observability
Grafana
DDD
Apache Kafka
Mocha
AWS
VueJS
ReactJS
Kubernetes
JWT
Microservices
RESTful API
CircleCI
Jest
NuxtJS
ACID
CI/CD
GitHub Actions
OAUTH2
LLM
Prometheus
ELK
Thông tin chung
- Thu nhập: Thỏa Thuận
Nơi làm việc
- Tòa nhà E.Town Central, Số 11 Đoàn Văn Bơ, Xom Chieu, Ho Chi Minh
Việc làm tương tự khác
Công Ty TNHH Money Forward Việt Nam
Xem trang công ty- Địa chỉ công ty: Tầng 21, Toà nhà E.town Central, 11 Đoàn Văn Bơ, Phường 12, Quận 4, Tp Hồ Chí Minh
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