AI Platform Engineer

Qualifyze; Barcelona; Hybrid; EUR 50,000 - 60,000; Full time

Benefits offered by this job

Hybrid working mode

Personal budget for development

Private health care

Meal allowances

All-company events in Europe

3 months remote work

Job summary

Qualifyze, founded in 2019, is a leading supplier-chain compliance company in Life Sciences. We are seeking an AI Engineer to join our Engineering team and bring AI solutions from prototype to production.

You will own AI solutions across their lifecycle, including architecture, deployment, monitoring and cost optimization. You will design and deploy production-ready LLM apps, evaluate models and manage cloud infrastructure with IaC.

Qualifications

• 4+ years in software/ML engineering or related field.
• 2+ years building and deploying LLM-based systems in production.
• Strong Python and backend API development experience.
• Experience with LLM solutions and techniques like RAG, embeddings, vector databases, and agent orchestration.
• Experience with cloud platforms (AWS/GCP) and their AI services.
• Practical experience with Docker, Kubernetes, CI/CD, and Infrastructure as Code (Terraform).
• Experience monitoring and operating AI/ML systems in production.
• Ability to communicate technical decisions clearly to both engineers and business stakeholders.
• Experience in regulated industries (pharma, life sciences, healthcare, or fintech) is a plus.
• Familiarity with LLM evaluation tools and LLMOps platforms is a plus.

Responsibilities

• Design, develop and deploy production-ready LLM applications, including RAG pipelines, agents and workflow automation.
• Evaluate and select models, frameworks and providers based on use case requirements.
• Develop evaluation processes to measure AI quality, reliability and regressions.
• Design and manage cloud infrastructure for AI workloads using AWS/Azure/GCP and IaC.
• Build and maintain CI/CD pipelines for models, prompts and AI services with automated testing and controlled releases.
• Deploy and scale AI services using containers and orchestration tools (Docker, Kubernetes).
• Implement monitoring and observability for AI systems (tracing, latency, drift).
• Establish usage controls and optimize costs via model selection, caching and batching.
• Investigate and resolve production issues across the AI stack.
• Stay updated with AI developments and identify practical tools for value.

Skills

Python

LLM experience

API development

Model evaluation

Cloud platforms

RAG/Embeddings

CI/CD

Infra as Code

Communication

AI governance

Education

4+ years in software/ML eng or related

Tools

Docker

Kubernetes

Terraform

AWS SageMaker / Vertex AI

MLflow / Langfuse

Vector DBs

OpenAI API

Job description

Founded in 2019, Qualifyze is a leading company in supply chain compliance management in the Life Sciences industry, trusted by over 1,500 pharmaceutical and healthcare companies globally. Our digital suite of solutions connects manufacturers, suppliers, and a global network of more than 250 auditors and quality experts.

With a track record of over 4,500 audits across 85+ countries and the largest and most accurate supplier network and data analytics tools, Qualifyze stands as the all-in-one partner for quality compliance and supply chain risk mitigation in the Life Sciences sector.

Role Overview

We are looking for an AI Engineer to join our Engineering team.

You will help bring AI solutions from prototype to production, building the systems, infrastructure and deployment processes behind our LLM-based and agentic applications. You will take ownership of AI solutions across their lifecycle, from architecture and development to deployment, monitoring and cost optimisation. You will also contribute to the technical practices that support AI development across the organisation.

Main responsibilities

• Design, develop and deploy production-ready LLM applications, including RAG pipelines, agents and workflow automation.
• Evaluate and select suitable models, frameworks and providers (e.g. OpenAI, Anthropic, Mistral and open-source alternatives) based on the requirements of each use case.
• Develop evaluation processes and benchmarks to measure AI quality, reliability and potential regressions before and after release.
• Design and manage cloud infrastructure for AI workloads using platforms such as AWS, Azure or GCP and Infrastructure as Code.
• Build and maintain CI/CD pipelines for models, prompts and AI services, including automated testing, controlled releases and rollback processes.
• Deploy and scale AI services using containers and orchestration tools such as Docker, Kubernetes or equivalent managed solutions.
• Implement monitoring and observability for AI systems, covering tracing, latency, output quality, drift and potential failure points.
• Establish usage controls and optimise costs through model selection, caching and batching.
• Investigate and resolve production issues across the AI stack.
• Keep up to date with developments in AI and identify techniques and tools that can bring practical value.

Main requirements

• 4+ years of experience in software engineering, ML engineering or MLOps/platform engineering, including 2+ years building and deploying LLM-based systems in production.
• Strong Python skills and experience developing production APIs and backend services.
• Practical experience with LLM solutions (e.g. OpenAI, Anthropic, Mistral or similar) and techniques such as RAG, embeddings, vector databases and agent orchestration.
• Experience with cloud platforms such as AWS or GCP and their AI services (e.g. Bedrock, SageMaker or Vertex AI).
• Practical experience with Docker, Kubernetes or equivalent technologies, CI/CD and Infrastructure as Code (e.g. Terraform or similar).
• Experience monitoring and operating AI or ML systems in production.
• Ability to communicate technical decisions clearly to engineering teams and business stakeholders.
• A structured and pragmatic approach to problem-solving, with a sense of ownership.
• Experience in regulated industries such as pharma, life sciences, healthcare or fintech is a plus.
• Familiarity with LLM evaluation tools and LLMOps platforms (e.g. Langfuse or MLflow) is a plus.
• Knowledge of AI governance, regulatory frameworks and IT security standards (e.g. EU AI Act, ISO 42001 and ISO 27001) is a plus.
• Experience developing internal tools or supporting developer enablement initiatives is a plus.
• Experience with agentic coding is a plus.

At Qualifyze, our salary ranges are transparent internally, and we aim to follow a similar approach externally. For this role, we’re happy to share a reference point within the band: the expected salary range is around 50,000 – 60,000 €, centered around the median.

Final compensation will depend on experience and performance during the process, with some flexibility within the range.

What do we offer?

• Competitive, annually reviewed compensation package
• Country vacation package that increases with your tenure
• Country-specific benefits offering incl. private health care, fitness and meal allowances
• Annual personal development budget to increase your impact
• Hybrid working mode, plus up to 3 months of the year work from anywhere.
• All the best kit and tools to work effectively
• Annual in-person all-company event and celebration in Europe
• Working with an exceptional team, doing some of the best work of your career

Use of AI in Our Recruitment Process

We believe in a human-led hiring process. All applications are reviewed manually by our Talent Acquisition team, and neither Talent Acquisition nor Hiring Managers use AI to screen, filter, rank, assess, or make decisions about candidates, including during interviews and assessments. During interviews, AI may be used only to support note-taking and transcription.

All hiring decisions are made by people!

Diversity & Inclusion at Qualifyze

At Qualifyze, we actively support the power of diversity, uniting complementary talents and perspectives to address new challenges. Our collective strengths help us find innovative solutions and turn difficulties into opportunities. We encourage you to bring your authentic self to work, fostering an inclusive environment where everyone belongs and feels heard.

We are an equal opportunity employer and welcome applications from candidates of all backgrounds, regardless of race, ethnicity, gender identity, sexual orientation, marital status, religion, disability, or age. Our hiring practices are rooted in fairness and respect, and we strive to create a culture where everyone feels valued and empowered.