At a Glance
- Tasks: Deploy advanced AI systems in real-world environments and lead technical delivery for enterprise customers.
- Company: Innovative BioTech startup focused on data science for drug discovery.
- Benefits: Competitive salary, fully remote work, flexibility, and autonomy.
- Other info: Join a dynamic team with opportunities for growth and collaboration.
- Why this job: Make a real impact with cutting-edge AI technology in the pharmaceutical industry.
- Qualifications: Experience with NLP, LLMs, and strong engineering skills.
The predicted salary is between 90000 - 130000 £ per year.
If you enjoy taking advanced AI systems out of the lab and into real-world enterprise environments, this role gives you the chance to do exactly that. You will work directly with highly technical customers, shaping how cutting edge NLP, knowledge graph, and LLM technology is deployed at scale, while still remaining deeply hands-on as an engineer.
They are a BioTech startup organisation building data science products that support faster and more informed drug discovery. Their platform processes vast volumes of scientific literature and structures it into high value, production-ready datasets used by global pharmaceutical organisations.
You will lead technical delivery for enterprise customers, owning implementations from initial trials through to production deployments. You will work closely with customer engineering and data science teams to understand their environments and design robust AI driven integrations. You will contribute to technical scoping during pre-sales, helping shape feasible and scalable solutions. Alongside customer work, you will contribute directly to internal platform and engineering initiatives.
- Strong commercial experience deploying NLP or LLM powered systems into production environments.
- Hands-on experience with retrieval augmented generation, vector databases, and retrieval or recommendation systems.
- Practical experience building, debugging, and operating end to end LLM workflows.
- A solid engineering mindset with comfort working across data platforms, APIs, and cloud infrastructure.
- Exposure to graph databases and modern data warehouses is highly beneficial.
- Confidence working in customer facing settings, explaining technical trade-offs and collaborating across technical and commercial stakeholders.
Base salary between £90,000 and £130,000, depending on experience + benefits. Fully remote working with flexibility and autonomy. The opportunity to work on high impact AI products used by leading enterprise customers.
AI Engineer (Remote) employer: Harnham
As a pioneering BioTech startup, we offer an exceptional work environment for AI Engineers looking to make a tangible impact in the field of drug discovery. Our fully remote setup promotes flexibility and autonomy, allowing you to collaborate with top-tier clients while contributing to innovative AI solutions that transform scientific literature into actionable insights. With a strong focus on employee growth and a culture that values hands-on engineering, you'll have the opportunity to lead technical projects and shape the future of AI in healthcare.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer (Remote)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend virtual meetups, and connect with potential colleagues on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving NLP, knowledge graphs, or LLMs. We want to see your hands-on experience, so make sure to highlight any real-world applications you've worked on.
✨Tip Number 3
Prepare for interviews by brushing up on technical concepts and practicing common interview questions. We recommend doing mock interviews with friends or using online platforms to get comfortable explaining your thought process and technical trade-offs.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace AI Engineer (Remote)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the AI Engineer role. Highlight your hands-on experience with NLP, LLMs, and any relevant projects you've worked on that showcase your ability to deploy AI systems in real-world settings.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about AI and how your background makes you a great fit for our team. Be sure to mention specific technologies or projects that relate to the job description, showing us you understand what we do.
Showcase Your Technical Skills:In your application, don’t shy away from detailing your technical expertise. Whether it’s your experience with vector databases or cloud infrastructure, make it clear how these skills will help you contribute to our mission of supporting drug discovery through AI.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our company culture and values!
How to prepare for a job interview at Harnham
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like NLP, knowledge graphs, and LLMs. Brush up on your understanding of retrieval augmented generation and vector databases, as these will likely come up during technical discussions.
✨Showcase Real-World Applications
Prepare to discuss how you've taken AI systems from concept to deployment in real-world settings. Be ready with examples that highlight your experience in building and debugging end-to-end LLM workflows, especially in enterprise environments.
✨Engage with Customer Scenarios
Since this role involves working closely with customers, think about how you would approach technical scoping and solution design. Prepare to explain how you would handle customer requirements and collaborate with engineering and data science teams.
✨Communicate Clearly and Confidently
Practice explaining complex technical concepts in simple terms. You’ll need to convey technical trade-offs to both technical and commercial stakeholders, so being able to communicate effectively is key. Mock interviews can help you refine this skill.
