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- Tasks: Lead the development of next-gen AI systems and applications that make a real-world impact.
- Company: Join Newpage Solutions, a top-rated digital health innovation company.
- Benefits: Enjoy competitive pay, flexible work options, and a supportive culture.
- Why this job: Be at the forefront of AI technology and transform healthcare with your skills.
- Qualifications: 7-12 years in software development, with strong AI/ML experience required.
- Other info: Collaborative environment with endless opportunities for growth and learning.
The predicted salary is between 43200 - 72000 £ per year.
We’re seeking a highly experienced, technically exceptional Lead AI Engineer to architect and deliver next-generation Generative AI and Agentic systems.
Location: Bristol, Hybrid | Type: Full-time
- Flexible and remote work
- Employee-centric culture
- Work-life balance
- Generous earnings
- Opportunities for growth
About Newpage Solutions
Newpage Solutions is a global digital health innovation company helping people live longer, healthier lives. We partner with life sciences organisations which include pharmaceutical, biotech and healthcare leaders, to build transformative AI and data driven technologies addressing real-world health challenges.
Your Mission
You will drive end-to-end innovation, from model selection and orchestration design to scalable backend implementation, all while collaborating with cross-functional teams to transform AI research into production-ready solutions. This is an individual-contributor leadership role for someone who thrives on ownership, fast execution and technical excellence. You will define the standards for quality, scalability and innovation across all AI initiatives.
What You’ll Do
- Develop AI Applications & Agentic Systems
- Architect, build and optimise production-grade Generative AI and agentic applications using frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, n8n, Pydantic AI or custom orchestration layers integrating with LLMs such as GPT, Claude, Gemini as well as self-hosted LLMs along with MCP integrations
- Implement Retrieval-Augmented Generation (RAG) techniques leveraging vector databases (Pinecone / ChromaDB / Weaviate / pgvector / etc), search engines such as ElasticSearch / Solr using both TF/IDF BM25 based full text search as well as similarity search techniques
- Implement guardrails, observability, fine-tune and train models for industry or domain specific use cases
- Build multi-modal workflows using text, image, voice and video
- Design robust prompt & context engineering frameworks to improve accuracy, repeatability, quality, cost and latency
- Cloud native deployments in hyper-scalers such as AWS / GCP / Azure using containerisation and orchestration with Docker / Kubernetes or serverless architecture
- Apply industry best engineering practices: TDD, well-structured and clean code with linting, domain driven design, security-first design (secrets management, rotation, SAST, DAST), comprehensive observability (structured logging, metrics, tracing), containerisation & orchestration (Docker, Kubernetes), automated CI/CD pipelines (Ex: GitHub Actions, Jenkins)
- AI Assisted Development, Context Engineering & Innovation
- Use AI-assisted development tools such as Claude Code, GitHub Copilot, Codex, Roo Code, Cursor to accelerate development while maintaining code quality and maintainability
- Utilise coding assistant tools with native instructions, templates, guides, workflows, sub-agents and more to create developer workflows to improve development velocity, standardisation, reliability across AI teams
- Focus on ensuring industry best practices to develop well-structured code that is testable, maintainable, performant, scalable and secure
- Partner with Product, Design and ML teams to translate conceptual AI features into scalable user-facing products
- Provide technical mentorship and guide team members in system design, architecture reviews and AI best practices
- Lead POCs, internal research experiments, and innovation sprints to explore and validate emerging AI techniques
What You Bring
- 7–12 years of total experience in software development, with at least 3 years in AI/ML systems engineering or Generative AI
- Experience with cloud native deployments and services in AWS / GCP / Azure with the ability to architect distributed systems
- A ‘no-compromise’ attitude with engineering best practices such as clean code, TDD, containerisation, security, CI/CD, scalability, performance and cost optimisation
- Active user of AI-assisted development tools (Claude Code, GitHub Copilot, Cursor) with demonstrable experience using structured workflows and sub-agents
- A deep understanding of how LLMs work, context engineering approaches and best practices with the ability to optimise accuracy, latency and cost
- Proven track record developing and deploying GenAI/LLM-based systems in production
- Advanced understanding of context engineering, prompt construction, optimisation and evaluation techniques
- End-to-end implementation experience using vector databases and retrieval pipelines
- Experience with GitHub Actions, Docker, Kubernetes and cloud-native deployments
- Are obsessed with clean code, system scalability and performance optimisation
- Can balance rapid prototyping with long-term maintainability
- Excel at working independently while collaborating effectively across teams
- Stay ahead of the curve on new AI models, frameworks and best practices
- Have a founder’s mindset and love solving ambiguous, high-impact technical challenges
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related technical discipline
Bonus Skills / Experience
- Understanding of MLOps, model serving, scaling and monitoring workflows (e.g., BentoML, MLflow, Vertex AI, AWS Sagemaker)
- Experience building streaming + batch data ingestion and transformation pipelines (Spark / Airflow / Beam)
- Mobile and front-end web application development experience
What We Offer
At Newpage, we’re building a company that works smart and grows with agility, where driven individuals come together to do work that matters.
- A people-first culture - Supportive peers, open communication and a strong sense of belonging
- Smart, purposeful collaboration - Work with talented colleagues to create technologies that solve meaningful business challenges
- Balance that lasts - We respect your time and support a healthy integration of work and life
- Room to grow - Opportunities for learning, leadership and career development, shaped around you
- Meaningful rewards - Competitive compensation that recognises both contribution and potential
Ready to Apply? Let’s build the future of health together.
Lead AI Engineer in Bristol employer: Newpage
Contact Detail:
Newpage Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead AI Engineer in Bristol
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the AI and tech scene. Attend meetups, webinars, or even local events. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to Generative AI and agentic systems. This is your chance to demonstrate your expertise and creativity, so make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions and be ready to discuss your past experiences in detail. Remember, confidence is key!
✨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 genuinely interested in joining our team at Newpage Solutions.
We think you need these skills to ace Lead AI Engineer in Bristol
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Lead AI Engineer role. Highlight your experience with Generative AI, cloud-native deployments, and any relevant projects that showcase your technical skills. We want to see how you fit into our mission!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about AI and how your background aligns with our goals at Newpage Solutions. Be genuine and let your personality come through.
Showcase Your Projects: If you've worked on any cool AI projects or have experience with tools like GitHub Copilot or Docker, make sure to mention them! We love seeing real-world applications of your skills, so don’t hold back.
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 you’re keen on joining our team!
How to prepare for a job interview at Newpage
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like Generative AI frameworks and cloud services. Brush up on your knowledge of LLMs, vector databases, and orchestration tools. Being able to discuss these topics confidently will show that you're not just familiar but truly passionate about the role.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles, especially those related to AI/ML systems. Use the STAR method (Situation, Task, Action, Result) to structure your answers. This will help you demonstrate your ability to tackle complex problems and innovate under pressure, which is key for a Lead AI Engineer.
✨Collaborate Like a Pro
Since this role involves working with cross-functional teams, be ready to share examples of how you've successfully collaborated in the past. Highlight your communication skills and how you’ve mentored others. This will show that you can lead and inspire a team while driving projects forward.
✨Stay Ahead of the Curve
Research the latest trends in AI and machine learning, especially those relevant to healthcare. Be prepared to discuss how emerging technologies could impact the industry and how you would leverage them in your role. This shows that you’re not just looking at the present but are also thinking about the future of AI in health.
