GenAI Infra Engineer: Scalable Tools & Data Pipelines

SIDRAM TECHNOLOGIES; United States; On-site; USD 140,000 - 190,000; Full time

Job summary

SIDRAM TECHNOLOGIES is seeking an AI Infra Engineer in the United States to own and evolve ML infrastructure for GenAI tools and data pipelines. You will build secure, scalable frameworks that enable non-engineering teams to run LLM analyses on sensitive data, with strong identity and auth controls.

You will migrate observability, maintain data pipelines, and collaborate to ship measurable efficiency gains.

Qualifications

• 5+ years in software/ML infrastructure engineering.
• Experience building GenAI tools for non-engineering teams.
• Experience with secure workflows and authentication.
• Experience labeling platform infrastructure.
• Experience migrating observability stacks to OpenTelemetry.
• Experience building data/ML pipelines across big data tools.
• Ability to partner with product and engineering to ship features with measurable efficiency gains.

Responsibilities

• Build full-stack internal GenAI tools (Python, FastAPI, Streamlit) for non-engineering teams to run LLM analyses on sensitive data, including scalable PII-masking pipelines.
• Design and maintain MCP servers/tools enabling teams to run workflows from AI chat clients with strict identity and auth checks.
• Own and evolve labeling platform infrastructure (FastAPI, Celery, Redis, Labelbox), including large-scale data migrations and on-call support.
• Migrate observability stacks from legacy tools to OpenTelemetry; build dashboards and ingests as code.
• Build and maintain data/ML pipelines (Airflow, Spark, Hive, Trino) supporting multiple business units.
• Partner with product and engineering leads to turn ambiguous problems into shipped features with measurable efficiency gains.

Skills

Python

ML infra

GenAI tooling

PII masking

OpenTelemetry

Tools

FastAPI

Streamlit

Celery

Redis

Labelbox

Airflow

Spark

Hive

Trino

Job description

SIDRAM TECHNOLOGIES is seeking an AI Infra Engineer in the United States to own and evolve ML infrastructure for GenAI tools and data pipelines. You will build secure, scalable frameworks that enable non-engineering teams to run LLM analyses on sensitive data, with strong identity and auth controls.

You will migrate observability, maintain data pipelines, and collaborate to ship measurable efficiency gains.