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
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Indicium AI.
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We think you need these skills to ace AI Engineers in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at Indicium AI, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Indicium AI. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Indicium AI
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Indicium AI!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
