Jobs / Qualifyze
AI Platform Engineer
Qualifyze · Barcelona, CT, Spain
Barcelona, CT, SpainExp: 4+ yrs50,000-60,000 EUR/yearlyHybrid
Remuneration
Competitive, annually reviewed compensation package; country-specific vacation package that increases with tenure; private health care, fitness and meal allowances; annual personal development budget.
Location
Barcelona, CT, Spain
Visa sponsorship
Not specified
Job summary
The AI Engineer builds and operates production LLM-based and agentic applications, taking solutions from architecture and development through deployment, monitoring, and cost optimisation. The role covers RAG pipelines, model evaluation, cloud infrastructure, CI/CD, container orchestration, and observability, using technologies such as Python, AWS, Azure or GCP, Docker, and Kubernetes. The systems support supply-chain compliance and risk mitigation in the life sciences sector.
Benefits
Vacation package that increases with tenurePrivate health careFitness and meal allowancesAnnual personal development budgetWork equipment and tools
Qualifications
- At least 4 years of software engineering, ML engineering, or MLOps/platform engineering experience, including at least 2 years building and deploying LLM systems in production.
- Strong Python skills and experience developing production APIs and backend services.
- Practical experience with LLM solutions, RAG, embeddings, vector databases, and agent orchestration.
- Experience with AWS or GCP and their AI services.
- Experience with Docker, Kubernetes or equivalent technologies, CI/CD, and Infrastructure as Code.
- Experience monitoring and operating AI or ML systems in production.
- Clear communication of technical decisions to engineering teams and business stakeholders.
- Experience in pharma, life sciences, healthcare, or fintech is a plus.
- Familiarity with LLM evaluation tools, LLMOps platforms, AI governance, regulatory frameworks, or IT security standards is a plus.
- Experience developing internal tools, supporting developer enablement, or using agentic coding is a plus.
Responsibilities
- Design, develop, and deploy production LLM applications, including RAG pipelines, agents, and workflow automation.
- Evaluate and select models, frameworks, and providers for different use cases.
- Build evaluation processes and benchmarks for AI quality, reliability, and regressions.
- Design and manage cloud infrastructure for AI workloads.
- Build and maintain CI/CD pipelines for models, prompts, and AI services.
- Deploy and scale AI services using containers and orchestration tools.
- Implement AI system monitoring and observability for tracing, latency, output quality, and drift.
- Control usage and optimise costs through model selection, caching, and batching.
- Investigate and resolve production issues across the AI stack.
- Track AI developments and identify useful techniques and tools.
Skills
AWSAzureDockerGCPKubernetesPythonTerraformDatadogGitHub ActionsGitLab CIGrafanaJenkinsOpenTelemetryPrometheus
Travel
Annual in-person company event in Europe
Industry
Life sciencesPharmaceuticalsHealthcareFintech
Relocation
No