At a Glance
- Tasks: Design and deploy cutting-edge AI systems using large language models.
- Company: Join a fast-growing AI consultancy trusted by top global enterprises.
- Benefits: Competitive salary, bonuses, personal learning budget, and flexible gear options.
- Other info: Dynamic environment with huge career growth opportunities and a collaborative culture.
- Why this job: Make a real impact in AI while collaborating with industry experts.
- Qualifications: Experience with LLM APIs, Python, and building production-grade applications.
The predicted salary is between 60000 - 80000 £ per year.
About Indicium AI
Indicium AI is trusted by the world's leading enterprises to deliver AI into production at scale. We are a global AI-native consultancy with proven experience across Financial Services, Energy & Utilities, Healthcare & Life Sciences, Retail & CPG, and Manufacturing. From strategy, to build, to business outcomes, we unlock value from AI with unmatched clarity, speed, and capability. Powered by 600+ AI experts serving 50+ enterprise clients from 5 global locations, we work side-by-side with top partners - including Anthropic, Databricks, AWS, OpenAI, and Microsoft - to deliver modern AI with speed and measurable impact.
Overview
We're seeking an experienced AI Engineer to design, build, and deploy production-grade AI systems powered by large language models. This role sits at the intersection of software engineering and AI implementation, focusing on building reliable, scalable applications rather than model training or research. You'll work with cutting-edge LLM technologies, building advanced AI systems that solve complex real-world problems through multi-agent orchestration, intelligent tool integration, and robust production workflows. You'll be crafting the orchestration layer that makes these systems production-ready—handling failure modes, optimizing agent collaboration, and ensuring consistent, reliable outputs at scale. You’ll combine strong software engineering fundamentals with deep practical knowledge of LLM capabilities, limitations, and best practices for building non-deterministic systems that users can trust.
Responsibilities
- Design and implement production AI systems integrating LLMs, RAG pipelines, vector databases, and agentic frameworks.
- Create evaluation frameworks to measure and monitor system performance, accuracy, and reliability.
- Build and maintain production-grade AI applications with clean code, appropriate error handling, APIs, and data pipelines.
- Experience implementing, maintaining and evaluating retrieval systems (vector/graph databases, ingestion pipelines, chunking strategies, retrieval techniques such as HyDE).
- Implement feedback loops and observability to continuously improve system performance.
- Craft effective prompts and optimize for latency, cost, and quality across different model providers and configurations.
Required Skills and Experience
- Hands-on experience building applications with LLM APIs and deep understanding of their capabilities, limitations, and failure modes.
- Practical implementation of RAG architectures, vector databases, knowledge graphs and prompt engineering.
- Experience building multi-step LLM workflows and agentic systems using frameworks (e.g. SDK, Strands, Claude Agents SDK, LangGraph, etc.) or custom implementations where needed.
- Strong Python (or other modern programming language) proficiency with production API/service development experience and cloud platform knowledge (AWS, GCP, Azure).
- Understanding of distributed systems, CI/CD, testing frameworks, and deployment pipelines.
- Solid foundations and understanding of production-grade, cloud-native platform and infrastructure requirements, design, and implementation.
- Strong data manipulation skills (pandas, SQL) and understanding of evaluation strategies for LLM-based systems.
- Ability to work with ambiguity and optimise non-deterministic systems through a process of experimentation and evaluation while balancing latency/cost/quality tradeoffs.
Nice to Haves
- Experience with AI-assisted coding using tools like Claude Code, OpenAI Codex, Github Copilot.
- Experience with fine-tuning LLMs for domain-specific applications and knowledge of when fine-tuning is preferable to prompt engineering or RAG.
- Experience with real-time streaming, multimodal models, or search technologies like Elasticsearch.
- Familiarity with model observability tools (LangSmith, Weights & Biases) and cost optimization strategies.
- Experience in specialized verticals (financial services, energy, healthcare, legal, retail) with understanding of compliance, security, and responsible AI practices.
- Experience with setting up tool calling agents, handoffs, and guardrails.
Why Indicium AI
- Fast-growing start-up organisation with huge opportunity for career growth.
- Highly competitive salary package along with company bonus.
- A hugely collaborative working environment where every person’s viewpoint is considered - a chance to make your mark on the business from day one!
- Financially backed business meaning security and support for new initiatives and global market expansion.
- Pick your own Gear! Macbooks, PCs, Accessories!
- Drive your development with a personal learning budget.
AI Engineers in London employer: Indicium AI
As a People Leader in Europe, you will join a dynamic and inclusive work culture that prioritises employee well-being and professional growth. Our commitment to competitive compensation, comprehensive benefits, and a supportive environment fosters engagement and retention, making us an exceptional employer in the UK and Portugal. With opportunities to shape our people strategy and collaborate with global leaders, you will play a pivotal role in driving our mission forward while enjoying the unique advantages of working in a fast-growing, international organisation.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineers in London
✨Tip Number 1
Network like a pro! Connect with folks in the AI space on LinkedIn or at industry 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 involving LLMs and AI systems. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common AI engineering questions and practical scenarios. Practice coding challenges and be ready to discuss your past projects in detail—this is your chance to shine!
✨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 AI Engineers in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the AI Engineer role. Highlight your experience with LLMs, RAG architectures, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Showcase Your Projects:Include links to your GitHub or any other portfolio showcasing your work with AI systems. We love seeing practical examples of your coding skills and how you've tackled real-world problems using AI technologies.
Be Clear and Concise:When writing your application, keep it straightforward and to the point. Use clear language to describe your experiences and achievements. We appreciate clarity and want to understand your journey without sifting through fluff!
Apply Through Our Website:Don't forget to submit your application through our official website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it makes the whole process smoother for everyone involved.
How to prepare for a job interview at Indicium AI
✨Know Your LLMs Inside Out
Make sure you have a solid understanding of large language models and their capabilities. Be prepared to discuss specific projects where you've implemented LLM APIs, and how you tackled challenges like failure modes or performance optimisation.
✨Showcase Your Coding Skills
Brush up on your Python or any other modern programming language skills. Be ready to demonstrate your experience in building production-grade applications, focusing on clean code, error handling, and API development. You might even be asked to solve a coding challenge during the interview!
✨Discuss Real-World Applications
Prepare examples of how you've designed and deployed AI systems in real-world scenarios. Highlight your experience with retrieval systems, multi-agent orchestration, and how you've crafted effective prompts to optimise for latency and cost.
✨Emphasise Collaboration and Adaptability
Indicium AI values a collaborative environment, so be ready to talk about how you've worked in teams to solve complex problems. Share experiences where you've navigated ambiguity and adapted your approach based on feedback or changing requirements.
