At a Glance
- Tasks: Deploy advanced AI systems in real-world environments and lead technical delivery for enterprise customers.
- Company: Innovative BioTech startup revolutionising drug discovery with cutting-edge AI technology.
- 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 on high-stakes AI products used by global pharmaceutical organisations.
- Qualifications: Experience with NLP, LLMs, and strong engineering skills in production environments.
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.
Remote AI Engineer 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. With a strong focus on employee growth and a culture that values hands-on engineering, you'll have the opportunity to shape cutting-edge technology in a supportive and dynamic atmosphere.
StudySmarter Expert Advice🤫
We think this is how you could land Remote AI Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the AI and biotech fields on LinkedIn or at industry events. We can’t stress enough how valuable personal connections can be when it comes to landing 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 love seeing practical examples of your work, so make sure to highlight any real-world applications you've tackled.
✨Tip Number 3
Prepare for technical interviews by brushing up on your engineering mindset. We recommend practising problem-solving scenarios related to data platforms and APIs. Being able to explain your thought process clearly will impress potential employers.
✨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’re always on the lookout for passionate candidates who want to make an impact in the AI space.
We think you need these skills to ace Remote AI Engineer
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. We want to see how you can bring your expertise to our team!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about deploying AI in real-world settings and how your background makes you a perfect fit for our BioTech startup. Let us know what excites you about the role!
Showcase Your Technical Skills:In your application, don't shy away from detailing your technical skills. Mention your experience with retrieval augmented generation, vector databases, and any cloud infrastructure you've worked with. We love seeing candidates who are hands-on and ready to dive into complex systems!
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 and culture!
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 experience with retrieval augmented generation and vector databases, as you’ll likely be asked to discuss how you've implemented these in past projects.
✨Showcase Real-World Applications
Prepare examples of how you've taken AI systems from concept to deployment in real-world settings. Be ready to explain your role in these projects, especially how you collaborated with technical teams and customers to deliver solutions that meet their needs.
✨Communicate Clearly and Confidently
Since this role involves customer-facing interactions, practice explaining complex technical concepts in simple terms. Think about how you would describe technical trade-offs to non-technical stakeholders, as this will demonstrate your ability to bridge the gap between engineering and commercial teams.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s current projects and future goals. This shows your genuine interest in their work and helps you understand how you can contribute to their mission of supporting drug discovery through AI.
