At a Glance
- Tasks: Lead AI system deployments and design robust integrations for enterprise customers.
- Company: Innovative BioTech startup revolutionising drug discovery with data science.
- Benefits: Competitive salary, fully remote work, flexible hours, and growth opportunities.
- Other info: Collaborative culture with clear paths for career advancement.
- Why this job: Make a real impact in AI while working on cutting-edge technology.
- Qualifications: Experience with NLP, LLM systems, 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.
The Company
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.
The Role
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 design and build solutions using retrieval systems, RAG architectures, agent based workflows, and APIs. You will contribute to technical scoping during pre-sales, helping shape feasible and scalable solutions. You will identify recurring customer needs and feed these back into the core platform, supporting productisation. Alongside customer work, you will contribute directly to internal platform and engineering initiatives.
Your Skills and Experience
- 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.
What They Offer
- 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.
- Clear scope to influence product direction and grow alongside a scaling, venture backed business.
- Additional benefits and development support within a collaborative, engineering led culture.
This role can't sponsor.
AI Forward Deployed Engineer employer: Harnham
As a BioTech startup, this company offers an exceptional opportunity for AI Forward Deployed Engineers to engage in meaningful work that directly impacts drug discovery. With a fully remote working environment, employees enjoy flexibility and autonomy while collaborating on cutting-edge AI products. The culture is deeply rooted in engineering excellence, providing clear pathways for professional growth and the chance to shape the future of innovative technologies in a supportive and dynamic setting.
StudySmarter Expert Advice🤫
We think this is how you could land AI Forward Deployed Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. The more you engage, the better your chances of landing that AI Forward Deployed Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to NLP, LLMs, and RAG architectures. This will give you an edge when discussing your hands-on experience during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of retrieval systems and APIs. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical stakeholders.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace AI Forward Deployed Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the AI Forward Deployed Engineer role. Highlight your experience with NLP, LLMs, and any relevant projects that showcase your skills in deploying advanced AI systems.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about taking AI out of the lab and into real-world applications. Mention specific experiences that align with the job description.
Showcase Technical Skills:Don’t forget to highlight your hands-on experience with retrieval systems, RAG architectures, and APIs. We want to see how you’ve tackled challenges in previous roles and what tools you used to overcome them.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates!
How to prepare for a job interview at Harnham
✨Know Your Tech Inside Out
Make sure you’re well-versed in NLP, LLMs, and RAG architectures. Brush up on your knowledge of retrieval systems and vector databases. Being able to discuss these technologies confidently will show that you’re not just familiar with the concepts but can also apply them practically.
✨Understand the Company’s Mission
Dive deep into the company’s focus on drug discovery and how their platform processes scientific literature. This will help you align your answers with their goals and demonstrate your genuine interest in their work. Plus, it’ll give you a chance to ask insightful questions during the interview.
✨Prepare for Customer-Facing Scenarios
Since this role involves working directly with customers, think about past experiences where you’ve had to explain complex technical concepts to non-technical stakeholders. Be ready to share examples that highlight your communication skills and ability to collaborate effectively.
✨Showcase Your Problem-Solving Skills
Be prepared to discuss specific challenges you’ve faced in deploying AI systems and how you overcame them. Use the STAR method (Situation, Task, Action, Result) to structure your responses, making it easy for the interviewer to follow your thought process and see your engineering mindset in action.
