AI Engineer

Location: London, with a minimum of 2 days per week onsite

Salary: £80,000–£120,000 per annum

Company

hirify.global delivers consultancy engagements focused on modern AI solutions, enterprise transformation, and reusable AI platform capabilities.

What you will do

• Build AI proofs of concept on real client data and deliver production-oriented POCs and MVPs.
• Develop RAG pipelines, agent architectures, LLM integrations, and protocol-driven tooling using MCP and tool orchestration.
• Iterate rapidly through frequent demos, feedback, and short development cycles.
• Engineer secure, scalable integrations with client technology estates, including guardrails, telemetry, and enterprise constraints.
• Create golden datasets, automated evaluation pipelines, accuracy monitoring, and drift monitoring to validate AI reliability.
• Extend the internal AI platform, codify field patterns into reusable assets, and lead technical upskilling sessions for clients and engineers.

Requirements

• Strong software engineering foundations, including clean code, testing, CI/CD, and a production mindset.
• Strong general-purpose programming skills in languages such as Python and TypeScript, with proficiency in at least two modern languages.
• Full-stack capability across frontend, backend, and data engineering.
• Hands-on production experience with LLMs and agents, including prompt engineering, agent workflows, RAG, tool orchestration, and MCP.
• Experience with evaluation frameworks, golden datasets, guardrails, and measuring AI performance.
• Client-facing delivery experience and the ability to work with enterprise security, compliance, and legacy integration constraints.

Nice to have

• Experience with vector databases, embeddings, or fine-tuning.
• Cloud experience with AWS or Google Cloud.
• Founder or startup experience.
• Open-source contributions or visible AI side projects.

Culture & Benefits

• Work in small delivery pods, typically alongside a Delivery Lead.
• Operate directly within client environments using real data and existing security and technology landscapes.
• Contribute to an internal AI platform and reusable Enablis assets between client engagements.
• Lead advanced technical sessions and support client engineer upskilling.