Applied AI Engineer

Applied AI Engineer

London, United Kingdom

Company overview

This early-stage startup has recently closed a heavily oversubscribed seed round from top-tier technology investors and is now preparing for its Series A. It is building AI-native workflows that enable industrial sectors such as aerospace, healthcare, manufacturing, and energy to operate with the speed and efficiency traditionally associated with software businesses.

Their platform combines large language models, document intelligence, and agentic workflows to automate complex operational processes that have historically depended on manual effort, fragmented systems, and unstructured data.

Role overview

This is a highly product-focused engineering role at the intersection of AI, software engineering, and real-world customer problem solving. You will design, build, and deploy production AI systems that directly power customer workflows. Rather than focusing on pure research or open-ended experimentation, you will apply LLMs, agents, evaluation systems, and document-understanding technologies to concrete operational problems in industrial environments.

The environment is fast-paced, highly autonomous, and ideal for engineers who enjoy ownership, ambiguity, and shipping quickly. You will work closely with founders, customers, and cross-functional teams to deliver customer-visible impact from day one.

What you’ll be doing

• Designing and deploying production-ready AI features across customer-facing products and internal workflows.
• Building and maintaining LLM-powered systems using structured outputs, tool/function calling, retrieval, and agent-based architectures.
• Developing evaluation frameworks to measure performance, detect regressions, and drive systematic model improvements.
• Working directly with customers to understand workflows, investigate failures, and continuously improve system reliability.
• Building document intelligence pipelines that extract and structure data from complex PDFs, forms, scans, and operational documentation.
• Designing orchestration layers that allow AI systems to execute multi-step workflows across multiple tools and data sources.
• Contributing across the stack to integrate AI capabilities into backend services and product experiences.
• Monitoring production performance and iterating rapidly based on real-world usage and customer feedback.
• Helping shape product direction by identifying where AI creates genuine value and where traditional software approaches are more appropriate.

What they’re looking for

• Strong Python engineering experience and solid software engineering fundamentals.
• Hands-on experience building and operating production AI systems beyond simple chatbot use cases.
• Deep familiarity with modern LLM platforms and APIs such as OpenAI, Anthropic, or Azure OpenAI.
• Experience with prompt engineering, structured outputs, function/tool calling, and model evaluation methodologies.
• Strong understanding of model behaviour, common failure modes, and techniques for improving reliability in production environments.
• Experience designing multi-step agent workflows and AI orchestration systems.
• Ability to work across backend services and product integrations to deliver end-to-end solutions.
• Strong product intuition and willingness to engage directly with customer problems.
• Comfort operating in a fast-moving environment with evolving requirements and minimal process overhead.

Nice-to-have experience

• Previous startup or founder experience, ideally within early-stage, venture-backed technology companies.
• Exposure to founder ecosystems such as Entrepreneur First, Y Combinator, Antler, or similar programmes.
• Experience building AI-native products from concept through to production deployment.
• A track record of thriving in ambiguous environments where ownership and initiative are expected.

Your first few months

• Ship production AI functionality within your first week.
• Own features end-to-end, from problem definition and model selection through to deployment, monitoring, and iteration.
• Work directly with customers to understand operational challenges and drive measurable product outcomes.
• Review large volumes of real-world outputs to uncover edge cases, failure patterns, and opportunities for improvement.
• Contribute meaningfully to both product and technical direction as the platform scales across industries and use cases.

Tech environment

• Python
• LLM APIs (OpenAI, Anthropic, Azure OpenAI)
• Agent frameworks and workflow orchestration
• Document intelligence pipelines and evaluation systems
• TypeScript, React
• Cloud infrastructure (major public cloud provider)

Package and benefits

• Highly competitive salary
• Meaningful equity package
• Visa sponsorship available
• Full relocation support to London
• Daily meals and office perks
• On-site working environment in central London
• Direct access to experienced founders and senior technical leaders
• High ownership and autonomy from day one
• Opportunity to help define the AI infrastructure underpinning large-scale industrial workflows