At a Glance
- Tasks: Lead the development of innovative AI solutions and manage technical partnerships.
- Company: Join Kintiga, a dynamic consultancy shaping the future of healthcare technology.
- Benefits: Competitive salary, extensive benefits, and flexible working for a better work/life balance.
- Other info: Work remotely with occasional travel; great career growth opportunities await!
- Why this job: Make a real impact in healthcare by architecting intelligent systems and driving innovation.
- Qualifications: Experience in AI, software engineering, and leading development teams.
The predicted salary is between 76023 - 95029 £ per year.
We are Kintiga (formerly MAP Patient Access, Axtalis, and SKC), a pan-European specialist consultancy that partners with ambitious health technology developers through the complex journey to achieve successful market access across Europe, with our tailored approach, global perspective and local expertise. Our clients in healthcare and life sciences are leading innovators in pharma, biotech, medtech, digital health, and diagnostics. As part of Kintiga, we support the successful launch and reimbursement of breakthrough therapies and technologies.
Join our team and help shape the future of the cutting-edge healthcare solutions. At Kintiga, we cultivate a collaborative and entrepreneurial culture where every voice matters. We value diversity, openness, and integrity - encouraging our team members to bring their ideas and passion to work every day. Become part of a supportive, dynamic team that thrives on innovation, lifelong learning, and making a meaningful impact in healthcare and life sciences.
Locations Suitable for Hire:
- UK&I – Remote, with occasional travel to London or Hannover.
- Germany – Remote but Hybrid preferred, Hannover – with occasional travel to London or Hannover.
- Belgium/Netherlands – Remote, with occasional travel to London or Hannover.
- Austria – Remote, with occasional travel to London or Hannover.
We are looking for an experienced Lead AI Engineer to provide hands-on technical leadership across our AI-driven products and platforms. This role combines deep software engineering expertise with practical application of AI / machine learning, and the ability to manage external AI development partnerships and provide technical direction to the wider delivery team and manage other developers. You will set technical direction, design and build production-grade AI solutions, and ensure high standards of security, scalability, and maintainability. You will work closely with product managers, analysts, users, and business stakeholders to turn ideas into reliable and impactful systems.
Responsibilities:
- Drive the development of cutting-edge AI solutions and bring your unique insights and experience into AI discussion.
- Be a major voice on buy-it vs build-it commercial decision-making and technical feasibility.
- Work with AI Suite Product Owners (stream leads) and the Chief Digital Officer (CDO) to maintain and plan roadmaps for existing and new AI Suite tools.
- Manage our AI solutions, lead the technical partnership with our primary AI development partner (reporting to CDO) and provide technical direction to the wider contractor and developer network.
- Stay up to date with latest AI technologies and contribute to in-house R&D.
- Ownership of AI services & projects, ensuring alignment with strategic goals.
- Propose, design and deploy production-grade AI systems including LLM-powered applications, RAG pipelines, and intelligent automation workflows, with ownership of Kintiga’s live AI Suite products (EPRI, SLR v2, PICSI) from a hands-on technical leadership & practical coding perspective, to enhance organisational and client delivery capabilities.
- Manage and take ownership of our CI/CD pipelines, automated testing, and cloud.
- Contribute to product roadmap planning and technical feasibility.
Qualifications:
- Proficiency in LLMs, Agentic AI, deep learning, NLP, and predictive analytics.
- Strong background in software engineering (e.g. Python, TypeScript or similar) and hands-on experience with LLM orchestration frameworks such as LangChain, LlamaIndex, or equivalent; familiarity with model training frameworks (TensorFlow, PyTorch) is useful but not a primary requirement.
- Experience in AI/ML platform technologies and services such as Azure ML/Sagemaker/Vertex, OpenAI, AutoML, OCR, STT, feature stores, vector databases.
- Implementation of AI/ML architectural patterns and best practices e.g. data drift detection, experimentation tracking, RAG, deployment models.
- Knowledge of database management systems (e.g. SQL, NoSQL) and basic data pipeline concepts.
- Proven experience leading development or engineering teams.
- Experience with cloud platforms (AWS, Azure, or GCP) with a preference for Azure.
- Solid understanding of API development & microservices architecture, CI/CD pipelines and release workflows, secure coding practices.
- Comfortable balancing hands-on delivery with strategic responsibilities.
Industry Experience: Hands-on experience in multiple industries with a focus on AI applications.
Partner Management: Experience managing or coordinating external AI development partnerships (specialist consultancies, academic labs, or vendor relationships) – including scoping work, reviewing delivery quality, and managing monthly capacity allocation.
Advanced Degrees: Higher education in AI or related fields (e.g. Master’s or PhD).
Certifications: Relevant professional certifications in AI, machine learning, or data science.
Experience working in regulated or data sensitive environments.
Domain Interest: Familiarity with pharmaceutical market access, HTA (Technology Assessment), or JCA (Joint Clinical Assessment) processes; or a demonstrable interest in learning this domain. Candidates with genuine curiosity about how AI outputs translate into regulatory submissions consistently outperform those without. This is a nice-to-have. We don't want to put off good talent from applying but it would divide those who at least research it before an interview.
Benefits:
- Competitive Salary (dependent on experience).
- Extensive benefit programme (varied on location).
- Exposure to an international work environment with cross-border project responsibilities.
- Flexible working – to maintain a better work/life balance.
You must have the right to work in UK and Ireland, Germany, Benelux, Austria or have a valid long-term working permit for the EU.
We’re a dynamic, solutions-focused team that brings together deep technical expertise and a commitment to excellence. If you’re a visionary Lead AI Engineer ready to architect intelligent systems, drive innovation, and shape scalable AI capabilities within a growing life sciences consultancy, we’d love to hear from you.
Last but not least: This role is full-time. We are unable to offer sponsorship for this role. If you are based in Germany, you will be required to provide a copy of your CV, Cover Letter and High School Diplomas.
Lead AI Engineer employer: Kintiga
At Kintiga, we pride ourselves on being an exceptional employer that fosters a collaborative and entrepreneurial culture, where every team member's voice is valued. With a focus on innovation and lifelong learning, we offer extensive benefits, flexible working arrangements, and opportunities for professional growth within the dynamic healthcare and life sciences sector. Join us in shaping the future of cutting-edge healthcare solutions while enjoying the advantages of remote work across multiple European locations.
StudySmarter Expert Advice🤫
We think this is how you could land Lead AI Engineer
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Kintiga!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Lead AI Engineer at Kintiga.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Kintiga.
✨Apply Directly through Our Website
When you find a suitable opening like Lead AI Engineer at Kintiga, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Lead AI Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Kintiga, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Kintiga. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Kintiga
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Kintiga!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
