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Описание вакансии
Текст:
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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