Lead Data Scientist – Agentic AI & GenAI Architect

Aria Intelligent Solutions; United Kingdom; On-site; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Private medical coverage

Vitality rewards

25 days annual leave

Wellbeing days

Volunteer day with donations match

Job summary

Aria Intelligent Solutions in the United Kingdom seeks a Lead Data Scientist to drive design, development, and productionization of Agentic AI, Generative AI, ML and Advanced Analytics solutions for real-world business problems. You will own end-to-end delivery from problem framing to deployment and mentoring.

The role requires hands-on leadership, strong foundations in statistics and ML, plus expertise in LLMs, RAG, tool calling and multi-agent systems.

Qualifications

• 8+ years of experience in Data Science, Machine Learning, AI or related areas.
• Strong foundation in Statistics, ML and Data Science.
• Hands‑on experience with Python and SQL.
• Significant experience with Generative AI / LLM applications.

Responsibilities

• Lead the design and development of production‑grade AI agents and agentic workflows.
• Architect agent architectures involving LLMs, tools, APIs, databases, business systems and external services.
• Build enterprise‑grade RAG solutions and retrieval architectures.
• Develop frameworks to evaluate AI systems for accuracy, reliability and business relevance.
• Mentor Data Scientists and AI Engineers and drive client alignment.

Skills

Python

SQL

Generative AI

LLMs

Agent orchestration

RAG

Embeddings

Docker

AWS/Azure/GCP

Client exposure

Leadership

Mentoring

Education

Bachelor's or Master's in CS/DS/Math/Engineering

Tools

FastAPI

PostgreSQL

Docker

Git

CI/CD

Job description

Aria Intelligent Solutions in the United Kingdom seeks a Lead Data Scientist to drive design, development, and productionization of Agentic AI, Generative AI, ML and Advanced Analytics solutions for real-world business problems. You will own end-to-end delivery from problem framing to deployment and mentoring.

The role requires hands-on leadership, strong foundations in statistics and ML, plus expertise in LLMs, RAG, tool calling and multi-agent systems.