Production AI Systems Engineer

Elios AI; Chicago (IL); On-site; USD 120,000 - 190,000; Full time

Job summary

Elios AI is hiring Forward Deployed Engineers to design and deploy production AI systems in real-world environments. This client-embedded role involves translating ambiguous business problems into robust software using LLMs, data infrastructure, and scalable architectures.

You will work across the full stack—from data pipelines and databases to APIs and frontend tooling—delivering systems that run in production with measurable impact and real-user feedback.

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 experience with prompt engineering and evaluation.
• Familiarity with LLM orchestration frameworks (LangChain, LangGraph, or similar).

Responsibilities

• Design and deploy LLM-powered applications using APIs (OpenAI, Anthropic, open-source models).
• Build agent-based systems and orchestrations.
• Develop evaluation pipelines for non-deterministic outputs.
• Build and optimize data pipelines using Airflow, Kafka, or similar.
• Design data models and integrate data sources.
• Work with data platforms such as Snowflake, Databricks, BigQuery, or Postgres.
• Implement caching, indexing, and retrieval strategies.
• Build scalable backend services and APIs (Python, FastAPI, Node.js, TypeScript).
• Deploy services using Docker, Kubernetes, and cloud platforms.
• Implement CI/CD pipelines and versioning.
• Manage secrets, auth, and secure integrations in production environments.

Skills

Python

TypeScript

Distributed systems

APIs

LLM integration

Data pipelines

Tools

Airflow

Kafka

Docker

Kubernetes

Snowflake

Databricks

BigQuery

Postgres

LangChain

LangGraph

Job description

Elios AI is hiring Forward Deployed Engineers to design and deploy production AI systems in real-world environments. This client-embedded role involves translating ambiguous business problems into robust software using LLMs, data infrastructure, and scalable architectures.

You will work across the full stack—from data pipelines and databases to APIs and frontend tooling—delivering systems that run in production with measurable impact and real-user feedback.