Senior Data/AI engineer

Luxoft · London, England ·

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Overview

In this role you design and deliver reusable data platform capabilities to enable quantitative researchers to discover, access, and use data across a complex landscape. You will work closely with cross-functional teams to translate business goals into scalable data pipelines and AI-enabled solutions.

You’ll drive data quality, lineage, and monitoring while adopting an AI-first approach to design, test, and deploy production-ready systems. This position offers the challenge of shaping a production-grade data platform that supports analytics, AI, and business applications.

You will operate in a fast-paced, collaborative environment to deliver measurable impact.

Responsibilities

  • Design, build, and enhance data pipelines and integration frameworks for AI, analytics, and business apps
  • Improve data quality, reliability, lineage, and monitoring
  • Implement AI-first approach with AI agents to design, build, test, and support solutions
  • Collaborate with business stakeholders, product managers, and engineering teams to translate objectives into technical solutions

Key requirements

  • 10+ years of professional software development
  • 5+ years of data engineering experience
  • Advanced Python proficiency for scalable backend services and data processing
  • Experience designing data pipelines, integration solutions, and large-scale architectures
  • Experience with relational databases and modern data storage technologies including graph, vector, or analytical platforms
  • Hands-on experience deploying AI/LLM-enabled applications in production
  • Experience with LangGraph, LangChain, agentic workflows, or compatible orchestration frameworks
  • Familiarity with modern AI tooling and AI-assisted software engineering practices
  • Experience operating in agile delivery environments
  • Strong communication with diverse stakeholder groups
  • Strong communication skills
  • Cross-functional collaboration
  • Problem solving
  • Python backend development
  • Data pipelines and integration
  • Large-scale data processing architectures
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