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- Tasks: Design and build cutting-edge AI systems using large language models.
- Company: Join a fast-growing AI consultancy trusted by top enterprises worldwide.
- 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, Python, and building production-grade applications.
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.
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, optimising 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 optimise for latency, cost, and quality across different model providers and configurations.
- 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.
- 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 optimisation strategies.
- Experience in specialised 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.
- 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 Engineer employer: Indicium AI
Contact Detail:
Indicium AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer
✨Tip Number 1
Network like a pro! Connect with folks in the AI space on LinkedIn or at meetups. We can’t stress enough how important it is to build relationships; you never know who might have the inside scoop on job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs and AI systems. We love seeing practical examples of what you can do, so make sure to highlight your best work.
✨Tip Number 3
Prepare for interviews by brushing up on common AI engineering questions and coding challenges. We recommend practicing with friends or using online platforms to simulate the interview experience—confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always on the lookout for passionate candidates who are ready to dive into the world of AI with us.
We think you need these skills to ace AI Engineer
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 do at Indicium AI!
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 value technical expertise!
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 shows you’re keen on joining our team at Indicium AI!
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 ready to discuss specific projects where you've implemented LLMs, focusing on the challenges you faced and how you overcame them.
✨Showcase Your Coding Skills
Prepare to demonstrate your Python proficiency and experience with production API development. Bring examples of clean code you've written, and be ready to explain your thought process behind error handling and data pipelines.
✨Understand the Business Impact
Be prepared to discuss how your work as an AI Engineer can drive business outcomes. Think about how you've previously measured system performance and reliability, and be ready to share metrics that highlight your contributions.
✨Ask Insightful Questions
During the interview, ask questions that show your interest in the company's projects and future direction. Inquire about their approach to multi-agent orchestration or how they handle non-deterministic systems, which will demonstrate your knowledge and enthusiasm for the role.