Applied AI Engineer (AI Automation)

Fusemachines•New York, NY

15h•Remote

About The Position

As an AI Automation Engineer, you will play a pivotal role in delivering high-quality, tailored AI and automation solutions that directly address client challenges and generate tangible value. You will lead technical implementation efforts, support ongoing engineering for retainer clients, and help build scalable, productized solutions that can be deployed across multiple clients.

Requirements

3 to 5+ years of experience in software engineering or applied systems development.
Demonstrated project experience building AI-driven and automation-based solutions using tools such as GPT APIs, workflow orchestration platforms, and embeddings.
Hands-on experience building end-to-end AI agent workflows, including phone trees, customer support bots, voice agents, or API-driven AI agents.
Experience with Model Context Protocol (MCP) servers, or strong interest and ability to ramp up quickly.
Familiarity with modern AI-native toolchains, such as n8n, Make, Vapi, Zapier, LangGraph, LlamaIndex Agents, OpenAI Assistants API, or similar platforms.
Strong experience with Python and related frameworks, including prompt engineering, RAG pipelines, and system integration patterns.
Proven ability to translate ambiguous business goals into autonomous AI workflows and production-ready implementations.
Experience supporting client relationships and managing multiple priorities in parallel.
Self-directed, collaborative, and comfortable balancing deep technical builds with fast, iterative prototyping.

Nice To Haves

Prior consulting experience or work in fast-paced startup environments is a plus

Responsibilities

Design, develop, and deploy tailored AI and automation solutions based on client-specific needs and objectives.
Translate ambiguous business problems into scalable, end-to-end AI workflows using Python, n8n (or similar tools), OpenAI APIs, and vector databases.
Build full end-to-end AI automations, including triggers, LLM logic, API calls, data storage, error handling, monitoring, and iteration.
Design and deploy AI agent systems, including multi-step workflows that call tools, interact with APIs, and operate autonomously.
Integrate with third-party AI tools and platforms to solve real-world problems such as customer service queues, phone routing systems, voice agents, and agent-driven workflows.
Act as a technical partner for retainer clients, owning solution delivery, refinement, and ongoing maintenance.
Own the deployment, iteration, and continuous improvement of AI agent systems across multiple client teams.
Create technical documentation, client demos, and internal playbooks to support reuse, scalability, and knowledge sharing.
Stay current on emerging AI tools, libraries, and methodologies to continuously improve solution quality and delivery speed.

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