Production AI Engineer (Client-Embedded)

Elios AI

Atlanta (GA)

On-site

USD 120,000 - 190,000

Full time

8 days ago

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Job summary

Elios AI in the United States is hiring Forward Deployed Engineers to build and deploy AI systems in real-world environments. This client-embedded engineering role focuses on turning ambiguous problems into production systems that integrate LLMs, data infrastructure, and operational workflows.

You will design multi-step agent workflows, orchestrate tools, and deploy services with Docker, Kubernetes, and cloud platforms.

Qualifications

  • 3–8+ years of software engineering experience.
  • Proficiency in Python and/or TypeScript.
  • Experience building distributed systems, APIs, and data-intensive applications.
  • Hands-on prompt engineering, RAG architectures, and vector search experience.
  • Familiarity with cloud infrastructure and containerized deployments.

Responsibilities

  • Design and deploy LLM-powered applications using APIs and open-source models.
  • Build agent-based systems and orchestration frameworks.
  • Develop evaluation pipelines for non-deterministic outputs.
  • Create data pipelines (batch + streaming) with Airflow, Kafka, or similar.
  • Design data models and integrate diverse data sources.
  • Implement scalable backend services and APIs (Python/TypeScript).
  • Deploy services using Docker, Kubernetes, and cloud platforms.
  • Establish CI/CD pipelines and versioning for models and prompts.

Skills

Python
TypeScript
Distributed systems
APIs
Data pipelines
CI/CD
Containers

Tools

Docker
Kubernetes
Airflow
Kafka
Snowflake
Databricks
BigQuery
Postgres
FastAPI
Node.js

Job description

Elios AI in the United States is hiring Forward Deployed Engineers to build and deploy AI systems in real-world environments. This client-embedded engineering role focuses on turning ambiguous problems into production systems that integrate LLMs, data infrastructure, and operational workflows.

You will design multi-step agent workflows, orchestrate tools, and deploy services with Docker, Kubernetes, and cloud platforms.

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