Senior AI Agent Engineer — Production Systems

Luxoft; United States; Remote; USD 150,000 - 210,000; Full time

Job summary

Luxoft is seeking a self-directed software engineer to help build the next generation of agented systems for a leading global hedge fund. You will design and build systems that combine LLMs, software engineering, data, search, and domain-specific tools, and help shape how these systems reason, retrieve, and execute in production.

The role involves designing agent workflows, building retrieval systems, and evaluating model choices, with hands-on work on Python/TypeScript services in cloud

Qualifications

• 7+ years of software engineering experience.
• Strong Python and .NET skills with production-grade systems.
• Hands-on TypeScript/JavaScript and modern web tech.
• Solid CS fundamentals including data structures and algorithms.
• Experience building distributed, service-oriented architectures.
• Familiarity with Docker, containers, cloud infra, and modern deployment.
• Knowledge of AI agents, orchestration, memory, and grounding (RAG).

Responsibilities

• Design and build agent workflows, orchestration, and execution frameworks.
• Develop retrieval and knowledge systems across structured and unstructured data.
• Evaluate and refine agent performance and behavior.
• Build distributed, production-grade services and APIs (Python/TypeScript).
• Evaluate new models, frameworks, and tools for production use.
• Diagnose and resolve complex production issues across the stack.
• Prototype ideas, test, and turn successful ones into production systems.

Skills

Python

C#/.NET

TypeScript/JavaScript

DSA fundamentals

Distributed systems

Docker

Kubernetes

AI agents design

RAG / retrieval

Cloud infrastructure

Tools

Docker

Kubernetes

Vector databases

Knowledge graphs

Job description

Luxoft is seeking a self-directed software engineer to help build the next generation of agented systems for a leading global hedge fund. You will design and build systems that combine LLMs, software engineering, data, search, and domain-specific tools, and help shape how these systems reason, retrieve, and execute in production.

The role involves designing agent workflows, building retrieval systems, and evaluating model choices, with hands-on work on Python/TypeScript services in cloud