Full Stack Developer

AI in this role

openailangchainhugging-facevertex-aitensorflowjaxmlflowsagemakerjasper

ml-ops

Code 81 is established in 2023, CODE81 operates autonomously from within the Technology Cluster of Ghobash Group as a highly agile services driven organization, committed to enabling future thinkers.

AI/ML Integration

Collaborate with AI/ML teams to understand and integrate models into live applications.
Deploy models using APIs, TensorFlow.js, ONNX, or direct embedding techniques.
Maintain model versioning, performance monitoring, and retraining pipelines (MLOps best practices).

Backend Development

Develop robust APIs and backend logic using frameworks like Node.js, Django, or Flask.
Design scalable architectures for handling AI model inputs/outputs and data flow.
Integrate databases (PostgreSQL, MongoDB, Redis) for data persistence and caching.

Frontend Development

Build dynamic, intuitive UIs using React, Angular, or Vue.js.
Visualize AI model outputs clearly for end-users (dashboards, predictive indicators, etc.).
Ensure UI responsiveness, accessibility, and performance across devices.

Infrastructure & DevOps

Containerize applications using Docker and orchestrate via Kubernetes.
Manage deployments on cloud platforms like AWS, Azure, or GCP.
Implement CI/CD pipelines and monitor system health in production environments.

2–4 years of professional experience in full-stack software development.
Strong programming skills in JavaScript/TypeScript (React, Node.js) and Python (Django, Flask).
Experience integrating AI/ML models via APIs or frontend embedding (e.g., TensorFlow.js).
Solid understanding of RESTful or GraphQL APIs and microservices architecture.
Familiarity with Git, Agile development, and continuous integration practices.

Preferred:

Hands-on experience with Generative AI, LLMs, or platforms like Hugging Face, OpenAI, or LangChain.
Exposure to MLOps tools like MLflow, SageMaker, Kubeflow, or Vertex AI.
Working knowledge of secure coding practices and AI ethics (e.g., data privacy, model fairness).
Experience with real-time systems and streaming data (Kafka, WebSockets).

Languages/Technologies: Java/J2EE, ReactJS, JQuery, JSON, HTML, JavaScript, CSS, PLSQL. Additional: Angular 7, VueJS, AngularJS. Frameworks: Spring Boot, Spring 4(MVC, ORM, AOP, SECURITY, Batch), Struts 2, Hibernate 3+. Database: Oracle 19c. Web Services: RESTful Web Services (JAX-RS), SOAP, JSON. Build Tool: Maven. Version Control : Bit Bucket. Development Tools: Eclipse STS, Jira, Tibco Jasper Report. Application Server: WebLogic Application server, Apache Tomcat Testing: Junit.

How we rate this

Full Stack Developer at Ghobash Group rates 88 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

ML OpsOpenAILangChainHugging FaceVertex AITensorFlowJaxMlflow

Questions you could be asked

How do you monitor a model once it's live, and how do you know it needs retraining?
Walk me through how you've used OpenAI in your day-to-day work.
What are the limits of LangChain that you've run into, and how did you work around them?
What's a project where you used Hugging Face hands-on?
Walk me through how you've used Vertex AI in your day-to-day work.

Adapt your resume

List these exact terms on your resume: ML Ops, OpenAI, LangChain, Hugging Face, and Vertex AI. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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