Talentpool for Full Stack Engineer

Jatis Mobile

Jakarta Pusat

On-site

IDR 669,600,000 - 1,116,000,000

Full time

15 hours ago
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Job summary

Jatis Mobile is seeking an AI Full Stack Engineer to design and deliver end-to-end AI-powered applications, bridging frontend, backend, and ML deployment.

You will own features from UI/UX to data pipelines, integrate LLMs and AI services, implement RAG and vector search, and ensure scalable, secure production-ready solutions across cloud platforms. Collaborate with data scientists, engineers, and product teams to ship AI-driven features.

Qualifications

  • Experience with modern frontend frameworks and API development.
  • Proficient in Python/Node.js/Go and REST/GraphQL.
  • Ability to integrate AI/ML models into production apps.

Responsibilities

  • Design responsive frontend interfaces using modern frameworks.
  • Build robust backend services, APIs, and data layers for AI features.
  • Integrate AI/ML models (LLMs, CV, recommender systems) into applications.
  • Implement RAG, vector search, embeddings, and agentic workflows.
  • Develop data pipelines feeding AI models and deploy with MLOps practices.
  • Collaborate with data scientists and product teams to deliver AI-driven features.
  • Write clean, maintainable code and participate in CI/CD.

Skills

Frontend
Backend

Education

Bachelor’s or Master’s in CS/Software Eng

Tools

Git
Testing
Observability

Job description

An AI Full Stack Engineer (also known as Full-Stack AI Developer or AI Application Engineer) builds complete, end-to-end AI-powered applications. This role combines traditional full-stack development (frontend + backend) with AI/ML integration, enabling the creation of intelligent, production-ready products like AI chatbots, recommendation systems, intelligent dashboards, RAG applications, and agentic AI tools.

You will own features from UI/UX to data pipelines and model deployment — bridging software engineering, machine learning, and cloud infrastructure.

This is a high-demand, versatile role ideal for modern tech companies, startups, and enterprises adopting generative AI.

Key Responsibilities
  • Design and develop responsive, user-friendly frontend interfaces using modern frameworks.
  • Build robust backend services, APIs, and data layers to support AI functionalities.
  • Integrate AI/ML models (LLMs, computer vision, recommendation engines) into production applications.
  • Implement Retrieval-Augmented Generation (RAG), vector search, embeddings, and agentic workflows.
  • Develop and optimize data pipelines that feed AI models (connecting to data lakes, warehouses, or real-time sources).
  • Deploy, monitor, and scale AI applications using MLOps practices, containerization, and cloud services.
  • Ensure performance, security, scalability, and ethical AI compliance (bias mitigation, data privacy).
  • Collaborate with data scientists, ML engineers, designers, and product teams to deliver AI-driven features.
  • Write clean, maintainable code and participate in code reviews, testing, and CI/CD pipelines.
Required Skills & Qualifications
  • Frontend: React.js / Next.js, Vue, Angular, TypeScript, Tailwind CSS or similar.
  • Backend: Python (FastAPI, Flask, Django), Node.js, or Go. Strong API development (REST, GraphQL).
AI/ML Integration
  • Experience with LangChain, LlamaIndex, Hugging Face, OpenAI/Anthropic APIs.
  • Basic model training/evaluation with PyTorch or TensorFlow.
Data & Infrastructure
  • SQL/NoSQL databases, data lakes/lakehouses.
  • Cloud platforms: AWS, Azure, GCP (especially AI services like Bedrock, SageMaker, Vertex AI).
  • Other: Git, testing (unit + integration), observability (Prometheus, LangSmith).
  • Experience: 3–7+ years in full-stack development, with at least 1–2 years in AI/ML integration.
  • Education: Bachelor’s or Master’s in Computer Science, Software Engineering, or related field.
Nice-to-Have Skills
  • Experience with LLMOps, AI agents, or multimodal AI.
  • Domain knowledge in specific industries (healthcare, finance, e-commerce, etc.).
  • Strong understanding of AI ethics, governance, and responsible AI practices.
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