Specialist, AI Engineer
Novartis is hiring a Specialist, AI Engineer in Prague, Czechia. Level rates it ; you can apply on Novartis.
Level's read on this job
- On Level's scale, this AI engineer role is Builds AI ●●●●: the job is building AI systems.
- The posting mentions Claude, Copilot and LangChain among its tools and skills.
- Level classes it as a mid-level role.
- Novartis has 856 other open roles on Level.
- Posted in the last few days.
AI in this role
Salary Range:
Kč750,050.00 - Kč1,392,950.00
Job Description Summary
Location: Prague, Czech RepublicWorking model: Hybrid
#LI-Hybrid
About the role
The Software & Workflows organization partners with scientists, data experts and AI specialists across Novartis Biomedical Research to transform scientific workflows and laboratory processes. Our ambition is to make advanced digital and AI capabilities usable, scalable and impactful, helping teams generate better insights, improve decisions and accelerate the discovery of innovative medicines.
As a Specialist AI Engineer in BR Data & Digital, Software & Workflows, you will build and ship production-ready generative and agentic AI solutions that accelerate biomedical research. Working on AWS, you will implement LLM-powered applications and agents, including RAG pipelines, tool-using agents, APIs and supporting backend services.
You will write clean, well-tested code under the guidance of senior engineers, use modern AI coding tools day to day, and help operationalize responsible, reliable AI. This is a role for a curious, learning-oriented engineer who wants to build hands-on depth in modern and AI-enabled engineering practices while contributing to solutions that meet high standards for quality, performance, security, compliance and reliability.
What you will work on
You will work on agentic AI for drug discovery, scientific workflow automation and lab-in-the-loop systems.
This includes building the agents, tools and services that help scientists find targets faster, automate routine research workflows and support the connection between AI predictions and wet-lab experiments.
Job Description
Key responsibilities
- Build production-ready generative and agentic AI features, including LLM applications and agents on AWS, owning them from implementation through testing and deployment.
- Implement LLM inference pipelines, including prompting, retrieval-augmented generation, tool and function calling, and structured output.
- Develop AI agents using agentic frameworks such as Strands, LangGraph, LangChain, CrewAI or similar, and integrate them into existing applications and workflows.
- Build secure APIs and containerized backend services for models, agents and tools.
- Contribute to evaluation and observability practices, including test sets, tracing, and monitoring of cost and latency.
- Follow good ML and MLOps practices, including reproducible pipelines, data, model and prompt versioning, and systematic evaluation.
- Apply DevOps fundamentals, including version control, automated testing, code review, containerization and CI/CD.
- Use AI coding tools, such as Claude Code, GitHub Copilot or similar, to improve throughput and code quality.
- Collaborate with engineers, scientists, data experts and AI specialists to deliver reliable and scalable AI-enabled solutions.
- Help ensure solutions meet required standards for quality, performance, security, compliance and reliability.
Essential requirements
- 3+ years of software engineering experience, including recent hands-on work building LLM-powered or ML applications.
- Strong Python skills and solid software engineering fundamentals, including testing, version control and CI/CD.
- Familiarity with DevOps and MLOps practices, including containers, CI/CD and reproducible, well-tested pipelines.
- Hands-on experience with LLM inference, including prompting, RAG, and tool use or function calling.
- Experience building and deploying services on AWS.
- Familiarity with at least one agentic framework, such as Strands, LangGraph, LangChain, CrewAI or equivalent.
- Ability to work effectively in a collaborative, multidisciplinary environment.
- Curiosity, learning orientation and a practical approach to solving complex technical problems.
Desirable requirements
- Exposure to Amazon Bedrock and/or Bedrock AgentCore.
- Experience with vector stores such as OpenSearch, pgvector or similar, and embeddings.
- Familiarity with AI coding assistants in a professional workflow.
- Experience in a regulated or life-science environment.
- Awareness of responsible AI practices, including evaluation, guardrails, monitoring, privacy and security considerations.
Rewards & Benefits
At Novartis, we're committed to reimagining medicine together and rewarding the people who make it happen.
Expected Annual Base Salary Range for role: 750,050.00 - 1,392,950.00 CZK Annual
The base salary offered is determined based on gender-neutral objectives, such as relevant skills, competencies and experience in accordance with the Novartis pay setting policy and upon joining Novartis will be reviewed periodically.
In addition to your base salary, you may be eligible for a performance-based bonus depending on certain performance parameters.
The rewards of being part of our team go far beyond base pay and incentives. We also offer a variety of competitive benefits in kind to help you thrive personally and professionally, such as insurance plans, retirement plans, wellbeing resources and global recognition programs. In addition, we provide flexible and hybrid working options, where possible, and a minimum of 14 weeks paid parental leave.
Pay equity is a fundamental principle of our employment policy and reflects our commitment to create a diverse, equitable and inclusive environment that treats all employees with dignity and respect, as outlined in our Code of Ethics.
Benefits and compensation may vary by country and are subject to local legal requirements, including provisions of collective bargaining agreements where applicable. A full overview of your compensation package, including any relevant collective bargaining agreement details applicable to your role based on your employment location and Novartis employer entity, will be communicated separately to you during the application process.
Commitment to Diversity and Inclusion
Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.
Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together? https://www.novartis.com/about/strategy/people-and-culture
Benefits and Rewards: Learn about all the ways we’ll help you thrive personally and professionally.
Read our handbook (PDF 30 MB)
Skills Desired
Back-End Development, Code Analysis, Device Drivers, Distributed Computing, Model-View-ViewModel (MVVM), Object-Oriented Design (OOD), Real-Time Operating Systems (RTOS), Representational State Transfer (REST), Simulation Software, Software Design, Software Documentation, Software Engineering, Software Testing, Terraform (Software), TypeScript, Unit Testing, Windows Presentation FoundationHow we rate this
Specialist, AI Engineer at Novartis rates 97 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in AI engineer jobs at this level
Pay
- Typical AI engineer job
- $183k
This posting doesn't list pay. Use the typical AI engineer figure when pay comes up. See AI engineer jobs
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you monitor a model once it's live, and how do you know it needs retraining?
- How do you think about the risk of an AI system in this kind of role failing silently?
- Walk me through how you've used Claude in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: RAG, AI agents, ML Ops, AI Safety, and Claude. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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