GenAI Engineer

Luxoft

United States

Remote

USD 170,000 - 260,000

Full time

14 days+

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Job summary

Luxoft is seeking a senior software engineer to design and maintain an enterprise-scale Generative AI platform in the United States. You will build scalable Python APIs with FastAPI and FastMCP, integrate OpenAI GPT and Anthropic Claude, and develop RAG pipelines with Pinecone or Milvus to power candidate insights and workflow automation.

You will own architecture, deployment, monitoring, and CI/CD, mentor teammates, and collaborate with product and stakeholders to translate requirements into

Qualifications

7+ years of experience in software engineering.
Proficiency in Python development and modern frameworks.
Expertise with FastAPI and FastMCP for scalable APIs.
Experience with OpenAI GPT and Anthropic Claude.
Familiarity with vector databases Pinecone / Milvus and RAG.

Responsibilities

Design, develop, and maintain scalable Python apps using FastAPI and FastMCP.
Build production-grade REST APIs and AI-powered services with security and reliability.
Develop AI solutions using LLMs such as OpenAI GPT and Anthropic Claude.
Design AI Agents, Plugins, Skills, and MCP-based integrations to automate workflows.
Build and optimize RAG pipelines with Pinecone or Milvus.
Create prompt frameworks and context-management strategies.
Own end-to-end AI solution lifecycle from architecture to production support.
Collaborate with product managers, architects, and stakeholders to translate requirements.
Implement monitoring, logging, observability, and performance improvements.
Mentor team members and participate in design discussions.

Skills

Python

FastAPI

OpenAI GPT

Anthropic Claude

LangChain

RAG Architecture

AI Agents

GitHub

Monitoring

Tools

FastMCP

Pinecone

Milvus

Docker

Azure

AWS

CI/CD

VS Code

Job description

Project Description

Designed and developed an enterprise-grade Generative AI platform using Python, FastAPI, FastMCP to automate recruitment workflows and provide intelligent candidate insights. Built scalable, production-ready APIs that integrated with OpenAI GPT and Anthropic Claude models for candidate screening, resume analysis, job matching, and automated recruiter assistance.

Implemented RAG (Retrieval-Augmented Generation) pipelines using vector databases such as Pinecone/Milvus to provide context-aware responses from enterprise knowledge repositories. Developed AI Agents and custom plugins/skills to automate candidate engagement, interview scheduling, talent recommendations, and workflow orchestration.

Owned the complete application lifecycle, including architecture design, API development, deployment, monitoring, observability, logging, and performance optimization. Leveraged AI-assisted development tools such as Claude, Codex, and VS Code to accelerate development, debugging, code reviews, and delivery.

Responsibilities

Design, develop, and maintain scalable, high-performance applications using Python, FastAPI, and FastMCP.
Build and deploy production-grade REST APIs and AI-powered services following best practices for security, performance, and reliability.
Develop and integrate Generative AI solutions using Large Language Models (LLMs) such as OpenAI GPT and Anthropic Claude.
Design and implement AI Agents, Plugins, Skills, and MCP-based integrations to automate business workflows.
Build and optimize RAG (Retrieval-Augmented Generation) pipelines using vector databases such as Pinecone or Milvus.
Create prompt engineering frameworks and context-management strategies to improve LLM response quality.
Develop end-to-end AI solutions covering architecture, implementation, testing, deployment, and production support.
Collaborate with product managers, architects, and business stakeholders to translate requirements into technical solutions.
Implement monitoring, logging, observability, and performance optimization for AI applications and APIs.
Ensure code quality through unit testing, code reviews, CI/CD pipelines, and adherence to software engineering best practices.
Evaluate and adopt emerging AI technologies, frameworks, and industry best practices.
Leverage AI-assisted development tools such as Claude, Codex, and VS Code to accelerate development, debugging, and delivery.
Troubleshoot complex technical issues and provide timely resolutions in production environments.
Mentor team members and contribute to technical design discussions and innovation initiatives.