Full Stack Engineer (Python)
Pubblicato il 23-09-2026 - Dicto AI in Palermo
We're looking for a full-stack engineer with strong Node JS / 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 (Nest JS, React, Type Script) Develop backend services and AI-driven features using Type Script 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 Postgre SQL, 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 Type Script 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 Postgre SQL 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