Remote AI Platform Engineer — Data Pipelines & LLM Ops

Speedcast; United States; Remote; USD 67,000 - 78,000; Full time

Job summary

Speedcast is seeking an AI Engineer (AI Platform & Data Engineering) to design and operate data pipelines powering AI apps. You will productionize LLM-based services, build APIs, and ensure secure, cost-aware, scalable deployments on AWS.

You’ll work closely with Data Engineering, Data Science, and DevOps to deliver reliable AI features across lakehouse platforms. You will also contribute to ingestion pipelines, data quality, governance, and platform improvements, while collaborating in an agile

Qualifications

• 3–5 years of software or data engineering experience with hands-on AI/LLM development.
• Proficient in Python and strong SQL skills.
• Experience building and maintaining production data pipelines.
• Experience integrating foundation model APIs (e.g., AWS Bedrock, OpenAI) into applications.
• Hands-on AWS experience and security best practices.
• Experience containerising applications using Docker.
• Experience building and operating APIs and backend services.
• Understanding of data quality and data governance practices.
• Experience using Git and Agile/Scrum environments.
• Strong analytical, problem-solving, and communication skills.

Responsibilities

• Design, build, and operate pipelines powering AI applications: ingestion, embedding, vector stores, retrieval services.
• Productionize LLM-powered apps as reliable services: APIs, container deployments, observability, access control.
• Integrate AI workloads with lakehouse: streaming and batch sources, query layers, time-series stores.
• Develop and maintain evaluation/logging/feedback infrastructure for AI in production.
• Contribute to core data engineering duties: data pipelines, quality, reliability, platform performance.

Skills

Python

SQL

AWS

Docker

APIs

Data pipelines

LLM integration

Git

Agile/Scrum

Communication

Tools

Lambda

S3

ECR

Glue

Docker

Job description

Speedcast is seeking an AI Engineer (AI Platform & Data Engineering) to design and operate data pipelines powering AI apps. You will productionize LLM-based services, build APIs, and ensure secure, cost-aware, scalable deployments on AWS.

You’ll work closely with Data Engineering, Data Science, and DevOps to deliver reliable AI features across lakehouse platforms. You will also contribute to ingestion pipelines, data quality, governance, and platform improvements, while collaborating in an agile