AI Engineer – Machine Learning

🌍 U.S. Citizenship, Must be a US Citizen

🕒 Full-Time - This role is a remote full-time position within the United States.

✈️This role may require up to 10-20% travel, including periodic travel to our offices for team collaboration, planning activities, and in-person meetings."

About the Role

We are hiring two AI/ML Engineers for an early-stage, high-growth AI infrastructure company. Our team is building an enterprise-grade platform and we need highly curious, hard-working self-starters.

1. You will own the design and delivery of complex, multi-service AI architectures involving agent orchestration, secure workflows and real-world operational constraints.

What You Will Do

1. Own the architecture, design, and implementation of full AI/ML systems, including: Multi-service, distributed system architecture, workflow and agent orchestration.
2. Proven experience designing and deploying complex agentic systems using LLMs.
3. Hands-on design with multi-agent orchestration, routing, and tool orchestration.
4. Building products and harness around AI models, harness engineering. Product Engineering.
5. Your work goes far beyond prompts or app-level features. You will architect platforms and sustainable AI infrastructure.
6. You will build real, production agents—not prototypes relying solely on framework abstractions.
7. End-to-End AI Infrastructure with Python, AWS, Typescript. MCP servers to connect to agentic services with response API, Pydantic outputs, tool calling, guardrails, LLM validation framework, etc..

Desired Qualifications

1. 4+ years working professionally as a Machine Learning Engineer or Data Scientist.
2. 1-2+ years building and deploying Agentic, ML / LLM-powered systems in production environments.
3. Degree in Computer Science, Computer Engineering, Data Science or similar.
4. Experience developing, deploying and productionizing supervised and unsupervised machine learning models.
5. Proficient with: Python, Claude, OpenAI, MCP, Agentic Workflows, tool calling, Evaluation frameworks, cache management, knowledge graphs, agentic harness, eval harness, model validation framework, LLM.
6. 📌Has built agentic systems or multi-agent setups, LangChain, LangGraph, Strands, ADK, or any orchestration framework.
7. Work across cloud environments (AWS, Azure, GCP)

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