At a Glance
- Tasks: Lead hands-on delivery of Generative AI systems and shape a new Centre of Excellence.
- Company: High-growth consultancy investing in innovative Generative AI solutions.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Dynamic role with a focus on collaboration and innovation.
- Why this job: Join a cutting-edge team and make a real impact with Generative AI technology.
- Qualifications: 3+ years in Generative AI or applied ML, with cloud-native experience.
The predicted salary is between 80000 - 100000 £ per year.
Location: UK (Hybrid – 1–2 days per week onsite)
Employment Type: Permanent
167 Solutions is partnering with a high-growth consultancy making a significant multi-year investment into Generative AI. You will be one of the core technical leaders, responsible for hands-on delivery from day one, while also helping shape a new Generative AI Centre of Excellence (CoE).
This is a 24/7 hands-on engineering role, building, testing, deploying, and iterating production-grade GenAI systems at enterprise scale. You will help define the technical direction, tooling, and engineering standards while actively writing code and shipping solutions.
- Design, build, and deploy Generative AI systems end to end – from use-case discovery through to production.
- Build Retrieval-Augmented Generation (RAG) pipelines using vector databases, embeddings, and enterprise data sources.
- Work extensively with open-source and commercial LLM ecosystems, including Hugging Face models and tooling.
- Implement prompt engineering, evaluation frameworks, and performance optimisation strategies.
- Architect secure, scalable GenAI solutions on AWS and GCP.
- Apply LLMOps / MLOps practices: versioning, monitoring, cost control, bias, and drift management.
- Work directly with clients to translate business problems into deployable AI solutions, not slide decks.
- Contribute to building internal IP, accelerators, and reusable frameworks as the CoE scales.
Minimum 3 years’ experience building and deploying Generative AI or applied ML systems. RAG architectures and vector databases. Cloud-native experience across AWS and/or GCP. Experience operating at Senior / Lead / Manager level, or as the go-to GenAI engineer on projects. Enterprise-scale builds with real users, real data, and real impact. Hybrid working that balances autonomy with collaboration.
Technical Industry Manager (m/w/d) in London employer: 167Solutions
At 167 Solutions, we pride ourselves on being an exceptional employer that fosters a dynamic and innovative work culture. Our commitment to employee growth is evident through our investment in cutting-edge Generative AI projects, providing you with the opportunity to be at the forefront of technology while working in a hybrid environment that promotes both collaboration and autonomy. Join us to not only advance your career but also contribute to meaningful solutions that have a real impact on businesses.
StudySmarter Expert Advice🤫
We think this is how you could land Technical Industry Manager (m/w/d) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to Generative AI. This is your chance to demonstrate your hands-on experience and technical prowess, so make it shine!
✨Tip Number 3
Prepare for interviews by practising common technical questions and scenarios. We recommend doing mock interviews with friends or using online platforms to get comfortable discussing your experience and problem-solving approach.
✨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 Technical Industry Manager (m/w/d) in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Technical Industry Manager role. Highlight your experience with Generative AI, cloud-native solutions, and any hands-on engineering projects you've led. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about Generative AI and how you can contribute to our Centre of Excellence. Be genuine and let your personality come through – we love seeing the real you!
Showcase Your Projects:If you've worked on any relevant projects, make sure to mention them in your application. Whether it's building RAG pipelines or deploying AI solutions, we want to know about your hands-on experience and the impact you've made.
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 shows us you’re keen to join our team at StudySmarter!
How to prepare for a job interview at 167Solutions
✨Know Your Generative AI Inside Out
Make sure you brush up on your knowledge of Generative AI systems, especially the hands-on aspects like building and deploying them. Be ready to discuss specific projects you've worked on, particularly those involving RAG architectures and vector databases.
✨Showcase Your Cloud Experience
Since this role involves working with AWS and GCP, be prepared to talk about your cloud-native experience. Highlight any projects where you've architected secure and scalable solutions, and don't forget to mention how you managed costs and performance.
✨Demonstrate Your Problem-Solving Skills
This position requires translating business problems into deployable AI solutions. Think of examples where you've done this in the past and be ready to explain your thought process. Use the STAR method (Situation, Task, Action, Result) to structure your answers.
✨Prepare for Technical Challenges
Expect some technical questions or challenges during the interview. Brush up on prompt engineering, evaluation frameworks, and MLOps practices. Practising coding problems related to these areas can give you a solid edge.
