Data/AI engineer with Python

Luxoft; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Luxoft is seeking an experienced data engineering leader to design, build, and optimize data pipelines and integration frameworks supporting AI, analytics, and business applications. The role emphasizes data quality, lineage, and monitoring, with an AI-first approach and collaboration with stakeholders across product and engineering teams.

You will work on scalable backend services and large-scale data processing architectures, leveraging modern data platforms and cloud-native tools in an agile

Qualifications

• 10+ years in professional software development, incl. 5+ years data engineering
• Advanced Python skills for scalable backend services and data processing
• Experience designing data pipelines, data integration, and large-scale data architectures
• Relational databases and modern storage including graph/vector/analytical platforms
• Production experience with AI/LLM-enabled applications
• Familiarity with LangGraph, LangChain, agents, or orchestration frameworks
• Knowledge of modern AI tooling and AI-assisted software engineering
• Experience operating in agile delivery environments
• Strong communication with diverse stakeholder groups

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 using AI agents for design, build, test, and support
• Collaborate with business stakeholders, product managers, and engineering teams to translate objectives into technical solutions

Skills

10+ years dev

5+ years data eng

Python backend

Data pipelines

Relational databases

AI/LLM production

LangGraph LangChain

AI tooling workflows

Agile delivery

Stakeholder comms

Tools

Databricks

Spark

Delta Lake

AWS

Job description

Project description

Build reusable platform capabilities and data products that let quantitative researchers discover, access, and consume data across a complex, disparate landscape, and then accelerate the good prototypes to production.

Responsibilities

• Design, build, and enhance data pipelines and integration frameworks supporting AI, analytics, and business applications.
• Improve data quality, reliability, lineage, and monitoring.
• Implement AI first approach: use AI agents as a primary tool to design, build, test, and support solutions.
• Collaborate closely with business stakeholders, product managers, and engineering teams to translate business objectives into technical solutions.

SKILLS

Must have

• 10+ years of professional software development, including 5+ years of data engineering experience.
• Advanced proficiency in Python, including experience building scalable backend services and data processing solutions.
• Strong hands-on experience designing and implementing data pipelines, data integration solutions, and large-scale data processing architectures
• Experience working with relational databases and modern data storage technologies, including graph, vector, or analytical data platforms.
• Practical experience building and deploying AI/LLM-enabled applications in production environments.
• Experience with LangGraph, LangChain, agentic workflows, or orchestration frameworks for AI applications; evaluations.
• Familiarity with modern AI tooling and workflows, including and AI-assisted software engineering practices.
• Experience operating in agile delivery environments.
• Strong communication skills and ability to interact efficiently with various stakeholder groups including business users.

Nice to have

• Experience with Databricks, Spark, Delta Lake, or similar modern data engineering platforms.
• Experience designing enterprise data lakes, lakehouses, or large-scale analytical platforms.
• Domain experience within Investment Management, Asset Management, Capital Markets, or Financial Services.
• Strong understanding of Fixed Income products and related investment workflows. Candidates with significant Fixed Income domain expertise will be considered highly valuable.
• Experience with Aurora, Neptune, and other AWS data services.Strong hands-on experience designing and implementing data pipelines, data integration solutions, and large-scale data processing architectures.
• Experience architecting, provisioning, and managing production infrastructure on AWS, including services such as ECS Fargate, Lambda, SQS, and related cloud-native technologies.
• Experience defining cloud architecture programmatically using Infrastructure-as-Code (IaC) tools such as AWS CDK or Terraform.