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Key skills for this role
6–9 years total experience
1–3+ years in hands-on GenAI / LLM application development (production use cases)
Strong hands-on experience with: LLMs (Claude, OpenAI, etc.) RAG pipelines and retrieval optimisation GPT + Agentic AI implementation experience
LLMs (Claude, OpenAI, etc.)
RAG pipelines and retrieval optimisation
GPT + Agentic AI implementation experience
Experience with: LangChain, LangGraph, or similar frameworks Agent orchestration and tool-calling architectures
LangChain, LangGraph, or similar frameworks
Agent orchestration and tool-calling architectures
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Deep understanding of: LLM limitations, evaluation, and optimisation strategies
LLM limitations, evaluation, and optimisation strategies
Strong Python/Pyspark engineering expertise (production-grade development) with proven API integration experience
Deep data analysis experience and handling large volume of data
Fabric/Azure Databricks/Snowflake data engineering integration skills
Good exposure to: Cloud platforms (Azure/AWS/GCP) SQL Containers, CI/CD, monitoring
Cloud platforms (Azure/AWS/GCP)
SQL
Containers, CI/CD, monitoring
Prior experience in one or more:
Data Engineering (ETL/ELT, pipelines, orchestration)
Data Science / ML lifecycle (especially NLP)
Analytics engineering / data products
Experience with fine-tuning techniques (LoRA, PEFT) or prompt tuning strategies
Experience with enterprise GenAI security & privacy practices (data masking, access control, compliance)
Familiarity with Azure AI ecosystem (Azure OpenAI, Azure AI Search, Fabric, etc.)
Exposure to agentic coding tools (e.g., Claude Code or similar environments)
Verified company details for this employer are not available yet.
Full-time
Senior · 6+ years experience
Hybrid
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