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About the Role

Design, build, and operate data systems for Decagon's AI products. Own critical data pipelines and storage layers, improve reliability and performance, and create scalable data solutions for engineers.

Responsibilities

• Design and implement high-throughput data pipelines and streaming systems with strong SLOs, clear runbooks, and actionable telemetry.
• Build and operate real-time and batch ingestion infrastructure using tools like Kafka, Flink, and Airflow.
• Own the analytical data layer, including schema design, query performance, and cost optimization across ClickHouse, BigQuery, or similar.
• Partner with research and product teams to architect data solutions, evaluate performance, and scale new features.
• Tune pipeline and query latencies: optimize data paths, apply smart caching/partitioning, and hit tight p95/p99 targets.
• Lead infrastructure-as-code (Terraform) and GitOps practices for data systems; reduce drift with reusable modules and policy-as-code.
• Participate in on-call and drive down toil through automation and elimination of recurring data issues.

Requirements

• 5+ years building and operating production data infrastructure at scale.
• Hands-on experience with Tier 1 data technologies: ClickHouse, Kafka (or MSK/Pub-Sub/RabbitMQ), and Flink or dbt.
• Proven track record meeting high availability and low latency targets across streaming and batch workloads.
• Excellent observability chops (OpenTelemetry, Prometheus/Grafana, Datadog) and strong incident response discipline.
• Clear written communication and the ability to turn ambiguous data requirements into simple, reliable designs.
• Experience with CDC tooling (Debezium) and orchestration frameworks (Airflow, Dagster, or Prefect).
• Familiarity with Spark or Dask for large-scale data processing.
• Experience with cloud data warehouses (Snowflake, BigQuery, Redshift, Databricks).
• Experience being an early data/platform/infrastructure engineer at another company.
• Strong Kubernetes experience (GKE/EKS/AKS) and multi-cloud exposure (GCP, AWS, Azure).
• Experience with customer-managed deployments.

Skills

• Data Infrastructure
• Data Pipelines
• Streaming Systems
• Kafka
• Flink
• Airflow
• ClickHouse
• BigQuery
• Terraform
• GitOps
• OpenTelemetry
• Prometheus
• Grafana
• Datadog
• Debezium
• Dagster
• Prefect
• Spark
• Dask
• Snowflake
• Redshift
• Databricks
• Kubernetes (GKE/EKS/AKS)
• GCP
• AWS
• Azure
• MSK
• Pub-Sub
• RabbitMQ
• dbt

Location

• In-office
• United States

Work Type

• Full-time
• In-office

Experience Level

• Senior
• 5+ years building and operating production data infrastructure at scale

Salary/Compensations

• $200K – $400K
• Offers Equity
• Competitive equity
• Final compensation may vary based on location within the United States

Benefits

• Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)
• Medical, Dental, and Vision benefits for you and your family
• Life Insurance and Disability Benefits
• Retirement Plan (e.g., 401K, pension)
• Parental Leave
• Fertility and family building benefits through Carrot
• Daily lunches and snacks in the office

About the Company

• Decagon is a leading conversational AI platform empowering every brand to deliver concierge customer experiences.
• Technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.
• Building a future where customer experiences are redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships.
• Backed by world-class investors including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures.
• An in-office company driven by a shared commitment to excellence and velocity.
• Company values: Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle.
• The Infrastructure team builds and operates the foundations that power Decagon: networking, data, ML serving, developer platform, and real-time voice.
• The Infrastructure team partners closely with product, data, and ML to deliver high-scale, low-latency systems with clear SLOs and great developer ergonomics.
• The Infrastructure team organizes around four focus areas: Core Infra, Data Infra, ML Infra, and Platform (DevEx).
• Company mission is to deliver magical support experiences with AI agents working alongside humans to resolve issues quickly and accurately.