Key skills
AWSAzureCloudGoogle Cloud PlatformPySparkPythonAIMLGenAILLMOpenAIClaudeRAGLangChainAgenticLangGraphData EngineeringGCPGoogle CloudLeadership
About this role
Role Overview
- Lead the design of enterprise-grade GenAI and agentic architectures
- Define reference architectures, reusable frameworks, and best practices for LLM applications
- Architect and oversee implementation of end-to-end RAG pipelines
- Drive scalability, reliability, cost optimisation, and performance across GenAI platforms
- Provide technical leadership in prompt engineering and agent workflows
- Partner with Data Engineering teams to ensure data quality and compliance
- Build and scale GenAI / Agentic AI Centre of Excellence
Requirements
- 15+ years of total experience in Data Engineering / Data Science / AI
- 3+ years of hands-on experience in LLM / GenAI solutions at scale
- Proven experience in architecture, solution design, and enterprise delivery
- Strong hands-on experience with LLMs (Claude, OpenAI, etc.)
- Experience with RAG pipelines and retrieval optimisation
- GPT + Agentic AI implementation experience
- Experience with LangChain, LangGraph, or similar frameworks
- Strong Python/Pyspark engineering expertise
- Good exposure to Cloud platforms (Azure/AWS/GCP)
- Prior experience in Data Engineering, Data Science / ML lifecycle
Tech Stack
- AWS
- Azure
- Cloud
- Google Cloud Platform
- PySpark
- Python
Benefits
- Health insurance
- Paid time off
- Professional development opportunities
- Flexible working hours