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- Tasks: Lead AI solutions and drive technical strategy in a dynamic environment.
- Company: Innovative tech firm in London with a hybrid work culture.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Why this job: Shape the future of AI while collaborating with top industry leaders.
- Qualifications: 7+ years in software engineering, with a focus on Generative AI.
- Other info: Join a team that values innovation and offers excellent career advancement.
The predicted salary is between 80000 - 100000 £ per year.
Permanent Hybrid in Central London
Competitive Salary
Candidates MUST have an active GitHub account to be considered for this role
Key Responsibilities
- Strategic & Architectural Leadership
- Define and own the technical vision and architecture for AI solutions across the organization
- Evaluate, select, and standardize AI technologies, frameworks, and third-party services
- Lead technical design reviews and make critical architectural decisions for complex AI initiatives
- Drive technical strategy for responsible AI, model governance, and production ML operations
- Partner with senior leadership (CTO, VPs, Directors) to translate business objectives into technical AI roadmaps
- Influence product and engineering strategy through technical insights and feasibility assessments
- Technical Expertise & Execution
- Act as the go-to technical expert for complex AI challenges across engineering teams
- Lead proof-of-concepts for emerging AI technologies and assess their production viability
- Build and deliver production-ready AI and Generative AI solutions using LLMs, RAG architectures, agents, and responsible AI practices
- Implement and maintain retrieval pipelines using embeddings, vector databases, hybrid search methods, and effective chunking strategies
- Use AI coding assistants such as Cursor, GitHub Copilot, and Claude Code to accelerate development while maintaining ownership of outcomes and documenting best practices
- Standards & Enablement
- Establish and enforce engineering best practices, coding standards, and quality benchmarks for AI development
- Improve internal AI development tooling, including shared libraries, SDKs, and reference implementations for RAG, tracing, prompt management, and evaluation
- Mentor engineers across all levels, conduct code reviews, and elevate engineering standards across the organization
- Lead internal enablement and capability-building activities across the organization
- Cross-functional Collaboration
- Collaborate closely with Product using a working-backwards approach, producing technical designs, breaking down work, and delivering iteratively
- Partner with Security, Legal, and Data teams to define AI policies, review risks, and ensure privacy, PII protection, and regulatory compliance
Skills, Knowledge and Expertise
Must Have:
- 7+ years of software engineering experience with 3+ years focused on production Generative AI and RAG systems
- Demonstrated experience architecting and scaling complex AI systems in production environments
- Proven track record of technical decision-making and architectural leadership with measurable business impact
- Deep technical expertise in LLMs, RAG, agentic workflows, prompt engineering, embeddings, vector databases, and hybrid search techniques
- Hands-on experience with leading LLM providers (Anthropic Claude, OpenAI), including model selection, evaluation, and optimization
- Expert-level Python development skills and fluency with AI coding assistants (Cursor, GitHub Copilot, Claude)
- Production experience with AWS cloud services and container orchestration (Kubernetes), including infrastructure design for ML workloads
- Strong technical communication skills with ability to influence senior stakeholders and drive consensus across teams
- Strong data engineering capabilities, including dataset creation, ETL development, and metrics definition
- Solid understanding of ML fundamentals, experimentation methodologies, and model performance optimization
Nice to Have
- Experience with model fine-tuning, RLHF, or custom training approaches
- Familiarity with MLOps platforms and experiment tracking tools
- Experience with infrastructure as code (Terraform, CloudFormation)
- Background in NLP research or open-source AI/ML contributions
Principle AI Engineer - Permanent - London/Hybrid - MUST Have An Active Github Account employer: Robson Bale Ltd
Contact Detail:
Robson Bale Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principle AI Engineer - Permanent - London/Hybrid - MUST Have An Active Github Account
✨Show Off Your GitHub
Make sure your GitHub account is up-to-date and showcases your best work. We want to see your projects, contributions, and any cool AI stuff you've built. This is your chance to shine, so don’t hold back!
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even just chat with folks on LinkedIn. We can help you find opportunities through our website, but personal connections can really make a difference.
✨Prepare for Technical Interviews
Brush up on your technical skills and be ready to discuss your past projects in detail. We recommend practicing coding challenges and system design questions, especially around AI and ML topics. Confidence is key!
✨Follow Up After Interviews
Don’t forget to send a thank-you email after your interviews! It shows your enthusiasm and keeps you fresh in their minds. We’re rooting for you, so keep that communication open and positive!
We think you need these skills to ace Principle AI Engineer - Permanent - London/Hybrid - MUST Have An Active Github Account
Some tips for your application 🫡
Show Off Your GitHub: Since having an active GitHub account is a must, make sure to highlight your projects and contributions. We want to see your coding skills in action, so include links to your best work that showcases your expertise in AI and software engineering.
Tailor Your Application: Don’t just send a generic CV and cover letter. We’re looking for candidates who can align their experience with our needs. Take the time to tailor your application to reflect how your skills and experiences match the responsibilities and requirements outlined in the job description.
Be Clear and Concise: When writing your application, clarity is key. Use straightforward language and avoid jargon unless it’s relevant. We appreciate well-structured applications that get straight to the point while still showcasing your personality and passion for AI.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re genuinely interested in joining the StudySmarter team!
How to prepare for a job interview at Robson Bale Ltd
✨Showcase Your GitHub Account
Since having an active GitHub account is a must for this role, make sure to highlight your contributions. Prepare to discuss specific projects you've worked on, especially those related to AI and Generative AI. This will demonstrate your hands-on experience and technical expertise.
✨Prepare for Technical Questions
Expect in-depth questions about AI architectures, LLMs, and RAG systems. Brush up on your knowledge of these technologies and be ready to explain your decision-making process in past projects. Use examples that showcase your ability to lead architectural decisions and influence product strategy.
✨Demonstrate Leadership Skills
This role requires strategic and architectural leadership, so be prepared to discuss how you've mentored others and established best practices in previous positions. Share specific instances where your leadership made a measurable impact on a project or team.
✨Collaborate Effectively
Cross-functional collaboration is key in this role. Think of examples where you've successfully partnered with different teams, such as Product, Security, or Data. Highlight your communication skills and how you’ve driven consensus among stakeholders to achieve project goals.