Full-Stack Engineer, AI Studio
On-siteLisbon, Lisbon, Portugal
Job Summary
Define component boundaries with product, UX, and architecture partners to clarify acceptance criteria and non-functional requirements. Design and implement accessible UI components using modern JavaScript or TypeScript frameworks, while building APIs, services, background jobs, and data integrations with Python, Node.js, Java, or C#. Integrate approved model inference, LLMs, RAG, and agent tools with input validation and human control. Implement layered unit, integration, and performance tests to diagnose cross-layer failures, utilizing CI/CD, infrastructure as code, and monitoring practices. Maintain indicators for availability, latency, and AI quality while applying identity, least privilege, and GxP controls.
Required Qualifications
- Master's degree and 4 to 6 years of Computer Science, IT or related field experience OR Bachelor's degree and 6 to 8 years of Computer Science, IT or related field experience OR Diploma and 9 to 10 years of Computer Science, IT or related field experience
- Demonstrated ownership of at least one production frontend, backend, API, data, integration, automation or AI-enabled component
- Strong hands-on proficiency in JavaScript or TypeScript, at least one backend language such as Python, Java, C# or Node.js, and SQL
- Ability to design, build, release, monitor, diagnose and maintain a defined production slice with limited guidance
- Independent ownership
- Sound technical judgment
- Disciplined production follow-through
- Strong analytical and troubleshooting skills across frontend, API, data, integration and AI layers
- Clear communication of design decisions, estimates, evidence, trade-offs, risks and support implications
- Effective collaboration with product, UX, business, architecture, ML, platform, security, quality and operations teams
- Ability to guide junior engineers and improve reusable engineering practices
- Experience with Next.js rendering patterns, reusable design systems, browser telemetry, frontend performance, complex data-intensive interfaces or accessible human-AI review workflows
- Experience with GraphQL, WebSocket, Kafka or other event platforms, durable workflows, outbox or saga patterns, stream processing, API gateways, graph/vector stores or complex integrations
- Experience with scikit-learn, PyTorch, TensorFlow, Hugging Face, model-serving APIs, RAG evaluation, agent orchestration, document intelligence, computer vision, BI or automation
- Experience with AWS, Databricks, Kubernetes, serverless services, infrastructure as code, OpenTelemetry, Prometheus, Grafana, Splunk, CloudWatch or feature management
- Experience in healthcare, life sciences, GxP, validated systems or another regulated environment
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