Senior AI Full Stack Engineer

Hyphen Connect

Barcelona, Spain

22 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience required

5 years minimum

Working hours

Regular working hours

Job source

www.indeed.com

Tech stack

Java (Programming Language) Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Software Quality Databases Data Architecture Cursor DevOps Python (Programming Language) Query Optimization Queueing Systems

+20 more

Redis Cloud Services Software Engineering SQL Databases TypeScript Web Applications WebSocket AWS Cdk ReactJS Large Language Models Reliability of Systems Backend Kotlin Event Driven Architecture Real Time Data Apache Kafka Front End Software Development Amazon Simple Queue Service (SQS) Terraform Microservices

Job description

Production Ownership: Design, architect, ship, and maintain scalable web applications and distributed backend microservices.
Full-Stack Development: Build modern, accessible user interfaces paired with robust, performant APIs and background workers.
Data Architecture: Design complex SQL schemas, write efficient queries, and optimize databases for real-time data ingestion and transactional consistency.
Infrastructure & Ops: Deploy, monitor, and maintain cloud services on AWS or GCP using CI/CD pipelines and infrastructure best practices.
AI-Augmented Engineering: Systematically integrate AI tools into your daily development workflow-maximizing velocity while applying rigorous verification to ensure system safety and accuracy.

Requirements

5+ years of professional software engineering experience owning production web applications end-to-end.
Frontend: Strong expertise in TypeScript and modern UI frameworks (React preferred).
Backend: Advanced proficiency in at least one backend ecosystem: Java/Kotlin, Python, or Go.
Databases: Strong SQL proficiency and deep experience with schema design for complex, real-time workflows.
Cloud & DevOps: Demonstrated experience deploying and operating applications on AWS or GCP.
AI Tool Fluency: Daily, critical usage of modern AI coding assistants (e.g., Copilot, Cursor, Claude Code). You know precisely where LLMs excel, where they hallucinate or fall short, and how to verify, test, and refine generated code., * Experience building or integrating custom LLM chains, agentic frameworks, or RAG pipelines.
Knowledge of web sockets, event-driven architectures, or queueing systems (e.g., Kafka, Redis, SQS).
Experience with Infrastructure as Code (e.g., Terraform, AWS CDK).