Senior Data/AI engineer

Luxoft; Irvine (CA); On-site; USD 160,000 - 230,000; Full time

Job summary

Luxoft is seeking an experienced Data Engineer to design and enhance scalable data pipelines and AI-enabled platforms. You will work closely with stakeholders to translate business objectives into robust technical solutions.

The role focuses on data quality, reliability, and monitoring, leveraging Python backend services and modern data platforms. Strong collaboration across teams is essential for success.

Qualifications

• 10+ years of professional software development including 5+ years data engineering.
• Advanced proficiency in Python for scalable backend services and data processing.
• Strong hands-on experience designing data pipelines and large-scale architectures.
• Experience with relational databases and modern data platforms (graph, vector, analytics).
• Practical experience building AI/LLM-enabled applications in production.
• Experience with LangGraph, LangChain, agentic workflows or orchestration frameworks.
• Familiarity with modern AI tooling and AI-assisted software engineering practices.
• Experience operating in agile delivery environments.
• Strong communication skills and ability to interact with diverse stakeholders.

Responsibilities

• Design, build, and enhance data pipelines and integration frameworks supporting AI and analytics.
• Improve data quality, reliability, lineage, and monitoring.
• Implement AI-first approaches and production-ready AI agents for solutions.
• Collaborate with business, product, and engineering to translate objectives into technical designs.

Skills

10+ years development

5+ years data engineering

Python backend

Data pipelines

Relational databases

Graph/Vector storage

AI/LLM in production

LangGraph/LangChain

AI tooling workflows

Agile delivery

Communication skills

Tools

Databricks

Spark

Delta Lake

AWS

ECS Fargate

Lambda

SQS

Terraform

AWS CDK

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.