Full-Stack Engineer (AI/ML & MERN Stack)
Pubblicato il 26-10-2026 - Dicto AI in Alba
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.