Data/AI engineer with Python

Luxoft; Irvine (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Luxoft is seeking a senior data engineering professional to design and build scalable data pipelines and AI-enabled solutions for production environments in the United States. You will collaborate with business stakeholders and engineering teams to deliver end-to-end data platforms that support AI-driven analytics and research initiatives.

The role emphasizes data quality, reliability, and lineage, with hands-on work across Python-based services, modern storage platforms, and cloud-native

Qualifications

• 10+ years of professional software development with 5+ years in data engineering.
• Advanced Python proficiency for scalable backend services and data processing.
• Experience designing data pipelines, data integration and large-scale processing.
• Relational databases and modern storage (graph, vector, analytics).
• Production experience with AI/LLM-enabled applications.
• Familiarity with LangGraph, LangChain or orchestration frameworks.
• Agile delivery and strong stakeholder communication.

Responsibilities

• Design, build, and enhance data pipelines and integration frameworks.
• 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

Python

Data engineering

Data pipelines

AI/LLM apps

Agile delivery

Communication

Relational databases

LangGraph / LangChain

Tools

Databricks

Spark

Delta Lake

AWS CDK

Terraform

ECS Fargate

Lambda

SQS

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.