Enterprise AI Deployment Engineer - Remote Contract

Elios, Inc.; Washington (District of Columbia); Remote; USD 120,000 - 180,000; Full time

Job summary

Elios, Inc. is seeking Forward Deployed Engineers to take AI from prototype to production. You will scope problems with the client, write code in Python, connect it to their systems, and own the deployment through launch.

Engagements are full-time contract with enterprise teams across industries. Some weeks involve backend work, others consulting, data framing, and communicating realistic outcomes to VPs. You will build, evaluate, and improve LLM-driven solutions in real environments.

Qualifications

• 4+ years writing production software with Python.
• Shipped at least one LLM-powered system to real users.
• Experience deploying on cloud platforms, and working with APIs, auth, logging, and CI/CD.
• Ability to evaluate LLM output beyond eyeballing results.

Responsibilities

• Sit in discovery with client stakeholders and translate goals into scoped work.
• Build LLM applications, agents, and retrieval systems in Python with real latency and security considerations.
• Connect models to client systems: APIs, data warehouses, internal tools, MCP servers where applicable.
• Write evals before completion and iterate based on results.
• Deploy on AWS, Azure, or GCP and own post-launch outcomes.
• Handle integration and cleanup tasks as part of engagements.
• Explain trade-offs to both technical and non-technical audiences in writing and in person.
• Share learnings with the team to accelerate future engagements.

Skills

Python

LLM-powered systems

APIs

Cloud deployment

Tools

AWS

Azure

GCP

Job description

Elios, Inc. is seeking Forward Deployed Engineers to take AI from prototype to production. You will scope problems with the client, write code in Python, connect it to their systems, and own the deployment through launch.

Engagements are full-time contract with enterprise teams across industries. Some weeks involve backend work, others consulting, data framing, and communicating realistic outcomes to VPs. You will build, evaluate, and improve LLM-driven solutions in real environments.