Senior Data/AI engineer

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

Job summary

Luxoft is seeking an experienced data engineer in London to design and operate scalable data pipelines and AI-enabled solutions. You will work across AI, analytics, and business applications, improving data quality, lineage, and monitoring while collaborating with stakeholders to translate objectives into technical outcomes.

The role requires a strong background in data processing architectures, modern data platforms, and an AI-first mindset, with substantial experience in cloud-native

Qualifications

• 10+ years of professional software development including 5+ years in data engineering.
• Advanced Python skills for scalable backend services and data processing.
• Proven ability to design and implement data pipelines and large-scale architectures.
• Experience with relational databases and modern data storage platforms.
• Hands-on production experience with AI/LLM-enabled applications.
• Familiarity with LangGraph, LangChain, and AI orchestration tools.
• Experience in agile delivery and effective stakeholder collaboration.

Responsibilities

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

Skills

Data engineering

Python

Data pipelines

SQL

AI/LLM workflows

Distributed systems

Agile methodologies

Stakeholder communication

Relational databases

Cloud platforms (AWS)

LangGraph

LangChain

Data quality & monitoring

Tools

Databricks

Spark

Delta Lake

AWS

ECS Fargate / Lambda

Terraform / IaC

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.