AI engineer

Luxoft Germany; Irvine (CA); Hybrid; USD 180,000 - 240,000; Full time

Job summary

Luxoft is seeking a senior software engineer and AI infrastructure architect to lead enterprise RAG pipelines and cloud infrastructure on AWS in Irvine, CA.

You will design scalable IaC pipelines, implement observability, and mentor teams while translating business goals into technical solutions.

Outstanding Python/TypeScript skills, LangGraph/LangChain, and deep AWS experience are required, with a proven track record in production AI/LLM deployments.

Qualifications

• 10+ years of professional software development experience.

Responsibilities

• Oversee the development of enterprise Retrieval-Augmented Generation (RAG) pipelines, semantic chunking strategies, and vector database integrations
• Implement strict evaluation and observability frameworks to monitor production latency, API costs, system drift, and model accuracy
• Drive the design, deployment, and ongoing maintenance of secure, scalable, and resilient cloud systems on AWS leveraging ECS Fargate, Lambda, SQS, Aurora, and Neptune
• Own the end-to-end infrastructure lifecycle by embedding robust Infrastructure-as-Code (IaC) and deployment pipelines directly within the development workflow
• Act as the primary technical liaison between business stakeholders, product managers, and the engineering team to translate strategic goals into technical realities

Skills

10+ years experience

Python (asyncio, FastAPI)

TypeScript (Next.js/React)

LangGraph/LangChain

AWS (ECS Fargate, Lambda, SQS)

IaC (AWS CDK, Terraform)

Aurora/Neptune databases

CLI tooling (Claude Code CLI, Copilot)

Agile / production AI deployments

Cloud security & observability

Tools

LangGraph/LangChain

AWS ECS Fargate

AWS Lambda

AWS SQS

Aurora

Neptune

AWS CDK

Terraform (Python/TypeScript)

Claude Code CLI

GitHub Copilot CLI

Job description

Project description

Luxoft is initiating the development of a solution designed to generate investment insights based on sales and research materials. The solution will leverage advanced Agentic AI capabilities to significantly reduce the time required to prepare for client meetings and improve quality of the insights.

Responsibilities

• - Oversee the development of enterprise Retrieval-Augmented Generation (RAG) pipelines, semantic chunking strategies, and vector database integrations
• - Implement strict evaluation and observability frameworks to monitor production latency, API costs, system drift, and model accuracy
• - Drive the design, deployment, and ongoing maintenance of secure, scalable, and resilient cloud systems on AWS leveraging ECS Fargate, Lambda, SQS, Aurora, and Neptune
• - Own the end-to-end infrastructure lifecycle by embedding robust Infrastructure-as-Code (IaC) and deployment pipelines directly within the development workflow
• - Act as the primary technical liaison between business stakeholders, product managers, and the engineering team to translate strategic goals into technical realities

SKILLS

Must have

• 10+ years of professional software development experience.
• Advanced proficiency in Python (asyncio, FastAPI) and TypeScript (Next.js/React, serverless execution layers)
• Hands-on experience building complex, stateful agentic workflows using LangGraph or LangChain
• Proven track record architecting, provisioning, and managing your own production infrastructure on AWS, specifically utilizing ECS Fargate, Lambda, and SQS
• Experience defining cloud architecture programmatically using advanced Infrastructure-as-Code (IaC) tools like AWS CDK or Terraform (Python/TypeScript preferred)
• Experience managing relational databases (preferably Aurora) alongside graph or vector backends (such as Neptune)
• Power-user fluency with advanced command-line AI interfaces (Claude Code CLI, GitHub Copilot CLI) with a deep understanding of prompt engineering and context window management
• Experience operating in an agile setting, deploying and maintaining AI/LLM applications in a live, enterprise-scale production environment
• Accountable for results, with excellent communication skills to mentor engineers and defuse technical friction

Nice to have

• - Highly desirable: experience with AgentCore, AWS Neptune, Amazon API gateway
• - Familiarity with ML fundamentals relevant to content generation (embeddings, tokenization, evaluation, fine tuning/LoRA, prompt+retrieval evaluation).