Overview
At QIAGEN, we are driven by a simple but powerful vision: making improvements in life possible.
We’re dedicated to revolutionizing science and healthcare for the better. From our entrepreneurial roots to our current global presence, we've grown into a force for positive change. With thousands of employees across six continents, collaboration is our greatest strength. We’re always striving to identify talented individuals to join our exceptional teams.
We have played a pivotal role in shaping modern science and healthcare, and we're just getting started. If you're someone who thrives on new challenges, values diversity and wants to make a tangible difference in people's lives, then QIAGEN is the place for you.
At QIAGEN, every day is an opportunity to make a real-life impact.
Join us, grow with us, and together, let's shape the future of biological discovery.
About the opportunity
Join QIAGEN Digital Insights, a global leader in bioinformatics software and knowledge solutions that help scientists transform complex molecular data into actionable biological insights. Our SaaS products — including OmicSoft, our Discovery Knowledge Base, Ingenuity Pathway Analysis (IPA), and QCI — give pharma, biotech, academic, and government lab customers worldwide the proprietary datasets, biological knowledge, and analysis algorithms they need to interpret human molecular (genomic) data. Today, customers access these capabilities primarily through our web UIs.
As an AI Engineer leading our agentic tool integration effort, your job is to change that: you will help design and build the tools and services that let AI agents — both external agentic AI accessing us via MCP, and internal AI orchestration within QIAGEN — successfully use our data, knowledge, and analysis capabilities without a UI. Authentication and access authorization for external MCP access are handled by an existing gateway layer; your work begins after that boundary. Your focus is turning UI-driven analytical workflows into clean, agent-native tools backed by our existing product APIs and services, and structuring their outputs so LLMs can reason over and act on them reliably.
You'll work closely with bioinformaticians, product owners, and application engineers, based out of our Cluj-Napoca site. We're looking for a strong Python engineer with genuine curiosity about life sciences, hands-on experience with agentic AI development, and good judgment about how to design software interfaces for AI consumers.
QIAGEN Romania offers a professional work environment, valuing work-life balance.
Your tasks:
Knowledge and Data Integration for Agentic Systems: Integrate and expose heterogeneous scientific and product data sources — including knowledge graphs, relational databases, metadata services, analysis outputs, and existing product APIs — so they can be reliably used by LLM-based agents and MCP tools. This includes designing knowledge graph structures, embeddings, and query interfaces, as well as query/response patterns for other data sources, that make relationships, identifiers, confidence, provenance, and ambiguity explicit — ensuring agents can discover, query, and reason over the data safely and predictably, whether the underlying source is a graph, a database, or an API.
Model and data for agentic systems: Partner with application engineers to build MCP servers and agent-orchestration tools to ensure models, datasets, and knowledge representations can be reliably surfaced to LLM-based agents. This includes structuring outputs, preserving provenance and confidence metadata, and flagging ambiguity so agents can request clarification rather than hallucinate an answer.
Software Engineering: Write well-documented, extensible software code that is easy to maintain and adheres to generally accepted programming standards and OOP practices.
Collaboration: Work cross-functionally with bioinformatics experts and software engineers to align AI solutions with customer requests, downstream tool requirements, and our company’s strategic goals.
Responsible and transparent AI: Ensure transparent reporting of AI methodologies, data provenance, and known limitations to maintain customer and public trust. Proactively address risks like model bias, data security, and intellectual property, with particular attention to how biological claims are traced and communicated when relayed through an AI agent rather than presented directly by a human analyst.
Your profile:
5+ years working as a Data Scientist or AI/ML Engineer, with experience turning AI/ML methods into reliable, production-ready capabilities used by real users or downstream systems.
Strong Python development skills, including asynchronous programming (async/await) and building REST APIs/microservices with frameworks such as FastAPI.
Hands-on experience building or integrating with at least one agentic AI framework (e.g., LangChain, LangGraph, or the MCP SDK), and direct experience building MCP servers
Expertise in data preprocessing, feature engineering, and model evaluation techniques
Experience integrating foundation-model APIs into applications or agentic workflows, including structured output design, retrieval/tool interfaces, and metadata such as confidence, provenance, or citations to support reliable downstream LLM reasoning.
Ability to own quality and evaluation for agentic AI systems, including tool-call correctness, structured-output validation, retrieval quality, provenance handling, regression testing, and failure-mode analysis.
Familiarity with source control and issue tracking systems and CI/CD workflows
Understanding of Deep Learning algorithms
Nice to have:
Developed full data-focused applications to analyze and process data
Worked with biological data (e.g., gene expression profiles, pathways, gene metadata, etc.)
Proficiency in graph-based analysis and network modeling, including experience with tools like NetworkX and Neo4j
Research experience in bioinformatics, AI, or drug discovery
What we offer
Bonus/Commission
Local benefits
Referral Program
Volunteer Day
Internal Academy (QIALearn)
Employee Assistance Program
Hybrid work (conditional to your role)
Our people are the heartbeat of everything we do. Passion drives us as we push boundaries to innovate and evolve. We inspire with our leadership and make an impact with our actions. We cultivate a collaborative, supportive environment where each individual and team can flourish. We champion accountability and encourage entrepreneurial thinking.
QIAGEN is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, or disability.
Skills Required
- Strong Python development skills, including asynchronous programming patterns (async/await)
- Experience building scalable microservices using FastAPI and Docker
- Expertise in MCP server development or protocol-driven system design and data API integrations (REST, GraphQL, custom authentication)
- Robust testing practices including unit testing, integration testing, and error handling
- Hands-on experience with LLM platforms (OpenAI, HuggingFace, Claude) including prompt engineering, token management, and structured outputs (e.g., Pydantic)
- Proven knowledge of retrieval-augmented generation (RAG), vector embeddings, and agentic AI workflows (e.g., LangChain, LangGraph)
- Solid understanding of NLP concepts (tokenisation, POS tagging, parsing) and familiarity with embedding models (Cross-Encoders, Bi-Encoders, sentence-transformers)
- Knowledge of core machine learning principles, model training and evaluation, dataset management, and experience with PyTorch or TensorFlow (or strong willingness to learn)
- Degree in Computer Science, Bioinformatics, or related discipline (or equivalent practical experience); experience with scientific/biological data advantageous
- Strong software engineering best practices: version control, CI/CD pipelines, and code review processes
QIAGEN Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about QIAGEN and has not been reviewed or approved by QIAGEN.
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Flexible Benefits — Flexible work options (hybrid or remote where roles allow), flexible hours, sabbaticals, and site-specific childcare support work–life fit. Programs are presented as available where roles allow, signaling adaptable benefit design.
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Wellbeing & Lifestyle Benefits — A global Employee Assistance Program for employees and immediate family, alongside broader wellbeing initiatives and community volunteering time, provides everyday support. Recognition for inclusive culture reinforces the emphasis on a supportive environment.
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Parental & Family Support — Paid parental leave positioned as above typical U.S. norms and family-oriented offerings (e.g., on-site childcare at some locations) enhance caregiver support. Reports of solid PTO and holidays further strengthen family time.
QIAGEN Insights
What We Do
QIAGEN is the leading global provider of Sample to Insight solutions that enable customers to gain valuable molecular insights from samples containing the building blocks of life. Our sample technologies isolate and process DNA, RNA and proteins from blood, tissue and other materials. Assay technologies make these biomolecules visible and ready for analysis. Bioinformatics software and knowledge bases interpret data to report relevant, actionable insights. Automation solutions tie these together in seamless and cost-effective workflows. QIAGEN provides solutions to more than 500,000 customers around the world in Molecular Diagnostics (human healthcare) and Life Sciences (academia, pharma R&D and industrial applications, primarily forensics).
