AI Workflow Architect - LLM, RAG & Agents (Hybrid)

Korn Ferry Group; Birmingham; Hybrid; GBP 83,000 - 109,000; Full time

Job summary

Korn Ferry is seeking an experienced AI Workflow Development Engineer in Birmingham to build AI-powered applications that automate complex operational processes.

The role focuses on LLMs, RAG and agentic AI to reduce manual effort across exception handling, reporting and decision-support workflows, collaborating with business stakeholders.

We expect hands-on experience with LangChain, AWS, and production-grade automation; hybrid work with 3-4 days onsite.

Qualifications

• Experience building AI/LLM applications beyond model experimentation.
• Commercial experience with LangChain.
• Strong AWS experience.
• Proven experience implementing RAG solutions.
• Experience developing agentic AI/workflows.
• Strong application development and workflow automation skills.

Responsibilities

• Build AI-powered workflows for exception handling, triage, categorisation and decision support.
• Develop agents capable of processing data-quality issues and natural-language exceptions.
• Build automation for operational and reporting workflows.
• Develop natural-language matching and classification capabilities.
• Build both proof-of-concept and production-ready LLM applications.
• Work with business and operations stakeholders to translate manual processes and decision points into automated workflows.
• Support future use cases including rule interpretation, transformation logic and code generation

Skills

AI/LLM development

LangChain

AWS

RAG

Agentic AI

Workflow automation

Application development

Tools

LangChain

AWS

Job description

Korn Ferry is seeking an experienced AI Workflow Development Engineer in Birmingham to build AI-powered applications that automate complex operational processes.

The role focuses on LLMs, RAG and agentic AI to reduce manual effort across exception handling, reporting and decision-support workflows, collaborating with business stakeholders.

We expect hands-on experience with LangChain, AWS, and production-grade automation; hybrid work with 3-4 days onsite.