Senior Staff Engineer (AI)

TL;DR

Senior Staff Engineer (AI): Building and shipping LLM-powered features in a complex, production-scale application with an accent on retrieval systems, agentic workflows, and evaluation frameworks. Focus on designing end-to-end RAG architectures, optimizing backend performance with FastAPI, and leveraging autonomous coding agents to accelerate development.

Location: Must be based in the United Kingdom

Company

hirify.global is a global digital engineering company that provides software development and technology consulting services.

What you will do

• Develop and deploy LLM-powered features within complex, production-grade applications.
• Design and implement end-to-end RAG systems, including vector databases and semantic search.
• Build and secure MCP servers at scale while managing multi-agent system applications.
• Collaborate cross-functionally with product owners and global teams to solve complex technical challenges.
• Utilize AI-assisted coding tools and autonomous agents to automate workflows and optimize engineering processes.
• Apply systems-level thinking to ensure high-quality, scalable, and secure backend solutions.

Requirements

• Must be based in the United Kingdom
• 8+ years of experience developing APIs with Python.
• 2+ years of hands-on experience developing and experimenting with LLMs.
• Strong proficiency in building REST APIs using FastAPI.
• Proven experience with generative AI solutions in production environments.
• Deep understanding of RAG systems, prompt engineering, and event-driven architectures.

Nice to have

• Experience with LLM guardrails and monitoring/observability tools.
• Familiarity with LLM frameworks like LangChain or LlamaIndex.
• Experience building evaluation harnesses, regression suites, and LLM-as-judge metrics.
• Background in developing AI/ML technologies for business-critical applications.

Culture & Benefits

• Opportunity to work on high-impact, production-scale AI projects.
• Collaborative environment with global teams across multiple time zones.
• Focus on continuous learning and staying current with emerging AI technologies.
• Emphasis on data-driven decision-making and engineering excellence.