Senior Full Stack Engineer

Neu-Linx, Inc.
Mundelein, IL, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Compensation
$190,000.0 - $250,000.0
Working hours
Regular working hours

Tech stack

Artificial Intelligence Relational Databases Distributed Systems Django Web Framework ReactJS Retrieval-Augmented Generation Flask (Web Framework) Large Language Models Backend Agentic-AI AngularJS Evaluation of Large Language Models
+1 more
Api Design

Requirements

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  • 5+ years of full-stack software engineering experience. \n

  • 3+ years of React, React.js or Angular experience. \n

  • 3+ years of Python backend development (Django, Flask or similar). \n

  • Hands-on experience building and deploying LLM-powered applications. \n

  • Strong API design, distributed systems and relational database experience. \n

  • Experience with agentic AI, tool calling, MCP, RAG or LLM evaluation frameworks. \n

  • Comfortable working with emerging AI technologies and taking ownership in a fast-moving environment. \n

Benefits & conditions

Neulinx have partnered with a high-growth, Series D-backed TravelTech company that’s transforming the $100bn+ travel industry through technology and AI.

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Following a recent $60m Series D funding round, the business is expanding its engineering team to build intelligent products that help thousands of travel entrepreneurs automate workflows, manage clients and scale their businesses.

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We’re looking for a Senior / Staff Full Stack Engineer (Applied AI) to help develop an AI-powered copilot, building production-grade AI agents, orchestration systems and intelligent automation tools.

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This is a hands-on, product-focused role offering significant ownership across the AI stack, from backend infrastructure and agent frameworks to user-facing applications.

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What you’ll be doing

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  • Building and scaling production AI agents that automate complex business workflows. \n

  • Developing MCP tools, LLM integrations and agent orchestration frameworks. \n

  • Designing reliable tool-calling workflows, streaming responses, retries and guardrails. \n

  • Building evaluation, observability and regression-testing systems to improve AI performance. \n

  • Developing full-stack features across Python backend services and modern frontend applications. \n

  • Working closely with Product and Design to take AI features from concept through to production. \n

  • Improving latency, scalability and reliability across AI-powered applications. \n

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