At a Glance
- Tasks: Design and deploy AI applications that make a real impact in life sciences.
- Company: Join Envision, a purpose-driven tech company focused on life-changing outcomes.
- Benefits: Hybrid work options, competitive salary, and a culture of growth and support.
- Other info: Opportunity for career growth in a dynamic and supportive environment.
- Why this job: Be part of a collaborative team delivering innovative AI solutions that truly work.
- Qualifications: 3+ years in data science or software engineering, with a focus on AI.
The predicted salary is between 36000 - 60000 £ per year.
Passionate about building real AI? Skilled with LLMs, RAG pipelines, or agentic AI? Ready to deliver AI that actually works, not just demos? If yes, this role is for you!
Work shouldn't just be something we do; it should have a purpose. At Envision, we believe in creating life-changing outcomes through the work we do with our clients, giving back to our communities, while creating a company culture where our people thrive. We believe success starts with a workplace where everyone feels valued, supported, and empowered to grow.
Being part of a collaborative team means there's no limit to what you can achieve. With us, you can be a part of a growing company you want to work for.
Our Vision: To unleash the power of combined intelligence to accelerate patient access to life-changing treatments.
Our Mission: Delivering smarter and faster solutions to create, communicate, and commercialize value for our clients.
Our Values: Excellence, People, Growth
The opportunity
We are looking for a pragmatic AI Engineer who can bridge solid software engineering practices with the fast-evolving landscape of applied AI. You will help design, build, and evaluate AI systems that are reliable, measurable, and useful - not just demos.
You will work closely with data scientists, software engineers, and product managers to ship AI solutions that make real impact. You believe in evaluation before hype, automation where it adds leverage, and simple systems that perform well in production in the life sciences industry.
This is a hybrid working opportunity from either our Cambridge, UK or Leiden, Netherlands office.
How will you make an impact at Envision Pharma Group?
Role responsibilities
- Develop and deploy AI-powered applications from prototype to production using modern LLM frameworks and APIs.
- Design evals and metrics that measure real-world performance (accuracy, latency, UX quality, safety).
- Build and optimize Retrieval-Augmented Generation (RAG) pipelines integrating vector databases and LLMs.
- Implement data pipelines, retraining workflows, and monitoring tools that keep models current and performant.
- Develop and implement context engineering strategies to improve output quality and control hallucination risks.
- Collaborate with product, platform, and infrastructure teams to understand business needs and build systems that scale and fail gracefully.
- Apply agentic AI patterns (tool use, planning, reflection loops) pragmatically, choosing the right level of complexity for each use case.
- Champion good engineering practices: code reviews, testing, observability, CI/CD, reproducibility.
- Ensure AI solutions meet security, compliance, and explainability standards.
Do you have what we are looking for?
Skills & expertise
- 3+ years of experience in data science or software engineering, ideally with 2+ years focused on AI engineering.
- Proficiency in Python and experience with LLM APIs (OpenAI, Anthropic, or similar services).
- Experience with GenAI frameworks and libraries (LangChain, LlamaIndex, Haystack, or Hugging Face Transformers).
- Experience with vector databases (such as Pinecone, FAISS, Weaviate) and RAG pipeline implementation.
- Proven ability to evaluate AI systems through custom evals, benchmarking, or data curation.
- Developed and deployed AI-powered applications end-to-end, overseeing all phases from initial concept, prototyping & design through implementation, testing, and production launch.
- Familiarity with agentic AI concepts (tool-use, planning, multi-step reasoning), with a practical sense for when simpler systems suffice.
- Strong grounding in software engineering principles (version control, modular design, testing) and commitment to measurement-driven iteration.
- Excellent communication skills and the ability to explain complex AI solutions to non-technical stakeholders.
- Strong understanding of AI ethics, bias mitigation, and responsible AI practices.
Nice to have
- Experience with model fine-tuning, knowledge graphs, or multi-modal AI systems.
- Familiarity with AWS services for scalable GenAI deployment and MLOps practices.
- Demonstrated experience in direct client communication.
Do you have the experience we are looking for? If so, explore your place at Envision today!
AI Engineer in Cambridge employer: Envision Pharma Group
At Envision Pharma Group, we pride ourselves on being an exceptional employer that fosters a culture of collaboration, growth, and empowerment. Our hybrid working model allows you to enjoy the flexibility of remote work while being part of a supportive team in our Wilmslow office, where your contributions directly impact the lives of patients worldwide. With a commitment to employee development and a focus on creating meaningful outcomes, you'll find ample opportunities to learn and thrive in your HR career with us.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer in Cambridge
✨Tip Number 1
Network like a pro! Reach out to folks in the AI field, attend meetups, and join online communities. The more connections we make, the better our chances of landing that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving LLMs or RAG pipelines. This gives us a chance to demonstrate our expertise beyond just a CV.
✨Tip Number 3
Prepare for interviews by practising common AI engineering questions and scenarios. We should also be ready to discuss how we can contribute to real-world applications, not just theoretical concepts.
✨Tip Number 4
Apply through our website! It’s the best way to ensure our application gets noticed. Plus, it shows we’re genuinely interested in being part of the Envision team.
We think you need these skills to ace AI Engineer in Cambridge
Some tips for your application 🫡
Show Your Passion:When you're writing your application, let your enthusiasm for AI shine through! We want to see that you’re not just skilled but genuinely excited about building real AI solutions that make a difference.
Tailor Your Experience:Make sure to highlight your relevant experience with LLMs, RAG pipelines, and any other specific skills mentioned in the job description. We love seeing how your background aligns with what we’re looking for!
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s necessary. Remember, we want to understand your skills and experiences without getting lost in the details.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Envision Pharma Group
✨Know Your AI Stuff
Make sure you brush up on your knowledge of LLMs, RAG pipelines, and agentic AI. Be ready to discuss specific projects you've worked on and how they relate to the role. This shows you're not just familiar with the concepts but have practical experience too.
✨Showcase Your Collaboration Skills
Since this role involves working closely with data scientists and product managers, be prepared to share examples of how you've successfully collaborated in the past. Highlight your communication skills and how you’ve navigated team dynamics to deliver impactful AI solutions.
✨Prepare for Technical Questions
Expect some technical questions that test your understanding of AI systems and software engineering principles. Brush up on your Python skills and be ready to explain your approach to building and optimising AI applications, including any metrics you've used to measure performance.
✨Emphasise Ethical AI Practices
With a strong focus on responsible AI, be ready to discuss your understanding of AI ethics and bias mitigation. Share your thoughts on how to ensure AI solutions are compliant and explainable, as this will resonate well with the company's values.
