Full-Stack Engineer
Pubblicato il 26-10-2026 - Dicto AI in Palermo
We’re looking for a full-stack engineer with strong NodeJS / Python experience, combined with solid MERN-stack development skills. This role mixes applied AI work, backend engineering, and full product delivery. You’ll work across data pipelines, APIs, model integration, retrieval-augmented generation (RAG) systems, and cloud-native deployments.
Responsibilities
- Build and maintain full-stack applications using the MERN stack (NestJS, React, TypeScript)
- Develop backend services and AI-driven features using TypeScript
- Help to maintain RAG pipelines, vector databases, embeddings workflows, and model-serving integrations
- Implement scalable APIs and microservices integrating ML or LLM-based components
- Deploy and manage services in AWS and/or GCP (compute, storage, networking, CI/CD)
- Work with PostgreSQL, Redis and Qdrant for structured and unstructured data
- Collaborate with product and technical teams to take AI-powered features from prototype to production
- Maintain quality, performance, and reliability across the stack
Required Skills
- Strong TypeScript experience for backend development and applied ML
- Hands‑on experience building RAG systems:
vector stores, retrieval layers, embedding models
- Solid understanding of LLM integration, prompt patterns, and model‑serving frameworks
- MERN‑stack experience with strong React proficiency
- Strong Node.js and Express experience for API development
- Proficiency with PostgreSQL and database‑schema design
- Experience deploying both traditional and ML workloads on AWS or GCP
- Good grasp of distributed systems, containers, and CI/CD workflows
Nice to Have
- Work across ML workflows: data ingestion, preprocessing, inference, and evaluation
- Experience with Haystack, or similar frameworks
- Exposure to GPU workflows, inference optimization, or fine‑tuning
- Familiarity with serverless environments
- Experience with observability tools across backend and ML systems
Profile
- Comfortable owning work across backend, frontend, and ML integration
- Able to move quickly between prototyping and production‑grade implementation
- Pragmatic, product‑oriented, and comfortable operating in ambiguous environments