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- Tasks: Design and develop AI applications that deliver real business value at speed.
- Company: Exciting tech client focused on high-impact AI solutions.
- Benefits: Competitive salary, flexible work schedule, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and automation.
- Why this job: Join a dynamic team and apply your skills in practical AI applications.
- Qualifications: 5+ years in software engineering with strong Python skills and cloud experience.
The predicted salary is between 70000 - 90000 £ per year.
Canary Wharf (4 days/week on-site). We are recruiting on behalf of an exciting end client who is building high-impact AI-powered applications that deliver real business value at speed — and they need engineers who think holistically, automate relentlessly, and are fluent in the fast-moving world of AI tooling and infrastructure. This isn't a research role. It's for seasoned engineers who are excited about applying AI in practical, scalable, and production-grade ways.
What You'll Be Doing
- Designing, developing, and maintaining production-grade AI applications using modern engineering practices (CI/CD, testing, observability, cloud-native).
- Building foundational platforms — conversational bots, AI-powered search, unstructured data processing, GenBI — that scale across the enterprise.
- Working in cross‑functional, embedded teams alongside business stakeholders to ship AI solutions fast.
- Evaluating and integrating LLMs, vector DBs, RAG patterns, and AI agents into robust applications.
- Championing automation across data ingestion, evaluation, model integration, and deployment.
- Contributing to internal tooling libraries and AI engineering best practices.
What Our Client Is Looking For
- 5+ years of professional software engineering experience, with a track record of shipping complex systems in production.
- Strong Python skills (preferred), or Java/similar; solid experience with microservices, APIs, and backend systems.
- Experience integrating ML models into production (LLMs via APIs, RAG, fine-tuning, embeddings, agents).
- Solid grasp of software architecture, cloud infrastructure (AWS, Azure, or GCP), and modern DevOps.
- Ability to move fast without sacrificing code quality or operational excellence.
- Hands‑on experience with LangChain, Haystack, Hugging Face, Weaviate, or similar AI/ML tooling.
- Experience with agentic frameworks: LlamaIndex, CrewAI, AutoGen, or similar LLM orchestration toolkits.
- Background in platform engineering or internal developer tools.
- Experience with unstructured data (documents, conversations, images) and transforming it into structured formats.
- Prior work in a forward‑deployed or embedded team model.
Generative AI Engineer employer: Venturi
Contact Detail:
Venturi Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Generative AI Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI field and let them know you're on the lookout for opportunities. Attend meetups or webinars related to generative AI to meet potential employers and showcase your passion.
✨Tip Number 2
Show off your skills! Create a portfolio that highlights your best projects, especially those involving AI applications. Make sure to include links to any relevant code repositories or demos so hiring managers can see your work in action.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions related to AI and software engineering. Practice coding challenges and be ready to discuss your past experiences with integrating ML models and building production-grade applications.
✨Tip Number 4
Don't forget to apply through our website! We have exciting roles that match your skills, and applying directly can give you an edge. Plus, it shows you're genuinely interested in joining our team!
We think you need these skills to ace Generative AI Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your 5+ years of software engineering experience and any relevant projects you've worked on, especially those involving AI applications.
Showcase Your Projects: Include specific examples of production-grade AI applications you've designed or maintained. We want to see how you've applied your Python skills and integrated ML models into real-world systems.
Be Clear and Concise: When writing your cover letter, get straight to the point. Explain why you're excited about this role and how your background in cloud infrastructure and DevOps makes you a great fit for our team.
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 don’t miss out on any important updates during the process.
How to prepare for a job interview at Venturi
✨Know Your AI Tools
Make sure you’re well-versed in the specific AI tools mentioned in the job description, like LangChain and Hugging Face. Brush up on how you've used these tools in past projects, as this will show your practical experience and readiness to hit the ground running.
✨Showcase Your Engineering Experience
Prepare to discuss your previous work with production-grade systems. Be ready to share specific examples of how you've shipped complex systems, focusing on your role in the process and the impact it had on the business.
✨Emphasise Collaboration Skills
Since the role involves working in cross-functional teams, highlight your experience collaborating with business stakeholders. Share stories that demonstrate your ability to communicate effectively and deliver AI solutions quickly while maintaining quality.
✨Demonstrate Automation Mindset
Talk about your approach to automation in your previous roles. Provide examples of how you've championed automation in data ingestion or model integration, as this aligns perfectly with what the client is looking for in a candidate.