Design and build agentic GenAI systems using modern frameworks such as LangChain, AutoGen or Atomic Agents, taking the lead on translating product needs into scalable AI solutions and delivering production-ready implementations
Job Summary
Design and build agentic GenAI systems using modern frameworks such as LangChain, AutoGen or Atomic Agents, taking the lead on translating product needs into scalable AI solutions and delivering production-ready implementations.
Develop and maintain knowledge integration pipelines, including RAG architectures, custom model fine-tuning, vector search, and other grounding methods to ensure our AI systems have the right context for accurate, relevant outputs.
Act as a hands-on expert for GenAI topics, mentoring peers, guiding solution architecture, and driving best practices in coding, testing, observability, and documentation across the organisation.
Matching Summary
Design and build agentic GenAI systems using modern frameworks such as LangChain, AutoGen or Atomic Agents, taking the lead on translating product needs into scalable AI solutions and delivering production-ready implementations.
Skills & Requirements
Must-have
agentic GenAI systems
LangChain, AutoGen, Atomic Agents
knowledge integration pipelines
RAG architectures, vector search
Python, robust software engineering
define evaluation strategies
build prototypes for production
Nice-to-have
transforming how people buy
driving digital innovation
hands-on expert for GenAI topics
mentoring peers, guiding architecture
Key Requirements
Degree in computer science, data science, engineering
Experience building agentic GenAI systems in production
Practical experience with RAG pipelines, vector databases