Назад
2 дня назад

Senior Data Infrastructure Engineer (AI)

200 000 - 400 000$
Формат работы
onsite
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Senior Data Infrastructure Engineer (AI): Building and operating high-throughput data pipelines, streaming systems, and analytical storage layers that power conversational AI products with an accent on reliability, low latency, and scalable data operations. Focus on optimizing p95/p99 pipeline and query performance, implementing Terraform and GitOps practices, and creating reliable data platforms for product and research teams.

Location: On-site in San Francisco or New York City, United States

Salary: $200,000–$400,000 base salary per year, plus equity.

Company

Decagon develops a conversational AI platform that enables enterprises to deliver personalized customer experiences through voice, chat, email, SMS, and other channels.

What you will do

  • Design and operate high-throughput data pipelines and streaming systems with strong SLOs, runbooks, and actionable telemetry.
  • Build real-time and batch ingestion infrastructure using Kafka, Flink, Airflow, and related technologies.
  • Own the analytical data layer, including schema design, query performance, and cost optimization across ClickHouse, BigQuery, or similar systems.
  • Partner with research and product teams to architect data solutions, evaluate performance, and scale new features.
  • Optimize data paths, caching, partitioning, and pipeline and query latency to meet demanding p95 and p99 targets.
  • Lead Terraform and GitOps practices, participate in on-call rotations, and automate recurring data operations.

Requirements

  • At least 5 years of experience building and operating production data infrastructure at scale.
  • Hands-on experience with ClickHouse, Kafka or equivalent messaging systems, and Flink or dbt.
  • Experience meeting high-availability and low-latency targets across streaming and batch workloads.
  • Strong observability and incident response skills with tools such as OpenTelemetry, Prometheus/Grafana, or Datadog.
  • Clear written communication and the ability to turn ambiguous data requirements into reliable designs.

Nice to have

  • Experience with Debezium, Airflow, Dagster, Prefect, Spark, or Dask.
  • Experience with Snowflake, BigQuery, Redshift, Databricks, Kubernetes, and multi-cloud environments.
  • Experience as an early data, platform, or infrastructure engineer.
  • Experience with customer-managed deployments.

Culture & Benefits

  • In-office environment focused on execution, innovation, customer needs, and technical excellence.
  • Medical, dental, and vision coverage for employees and families.
  • Life insurance, disability benefits, retirement plan, parental leave, and fertility and family-building support.
  • Monthly wellness and lifestyle stipend, daily office lunches and snacks, and a flexible vacation policy subject to local requirements.

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