At a Glance
- Tasks: Design and build 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 leaders.
- Qualifications: Experience with LLM APIs, strong Python skills, and cloud platform knowledge.
The predicted salary is between 36000 - 60000 £ per year.
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 London employer: Indicium Tech
Indicium AI is an exceptional employer, offering a unique opportunity to work at the forefront of AI engineering in London. With access to cutting-edge tools and a collaborative culture that prioritises employee growth, you will lead a high-performing team while engaging directly with senior clients across diverse sectors like Financial Services, Energy, and Healthcare. The company fosters an environment of innovation and excellence, ensuring that your contributions not only shape the future of AI but also advance your career in a meaningful way.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineers London
✨Tip Number 1
Network like a pro! Reach out to current employees at Indicium AI on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for landing a role as an AI Engineer.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs and production-grade AI systems. This will give you a leg up during interviews and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python skills and understanding of cloud platforms. Practice coding challenges that focus on building APIs and working with data pipelines to impress the interviewers.
✨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, it shows you’re genuinely interested in joining the team at Indicium AI.
We think you need these skills to ace AI Engineers 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 as much as we appreciate technical skills!
Apply Through Our Website:Don’t forget to submit your application through our 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 Tech
✨Know Your LLMs
Make sure you brush up on your knowledge of large language models. Understand their capabilities, limitations, and failure modes. Be ready to discuss how you've implemented them in past projects, as this will show your practical experience and depth of understanding.
✨Showcase Your Coding Skills
Since strong Python proficiency is a must, be prepared to demonstrate your coding skills during the interview. You might be asked to solve a problem on the spot or discuss your previous projects. Bring examples of clean code you've written and be ready to explain your thought process.
✨Discuss Real-World Applications
Prepare to talk about how you've built production-grade AI systems that solve real-world problems. Highlight your experience with multi-agent orchestration and intelligent tool integration. This will help the interviewers see how you can contribute to their projects right away.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company's approach to AI implementation, their tech stack, or their future projects. This shows your genuine interest in the role and helps you assess if it's the right fit for you.
