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Decagon

Senior Software Engineer, Data Infrastructure

  • Office
  • 6+ years

Salary

$200,000 - 400,000/ year

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Description

About Decagon

Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.

Our 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.

We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.

We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.

The Infrastructure team builds and operates the foundations that power Decagon: networking, data, ML serving, developer platform, and real‑time voice. We partner closely with product, data, and ML to deliver high‑scale, low‑latency systems with clear SLOs and great developer ergonomics.

We organize around four focus areas:

Core Infra: The foundational cloud stack—networking, compute, storage, security, and infrastructure‑as‑code—to ensure reliability, scale, and cost efficiency.

Data Infra: Streaming/batch data platforms powering analytics/BI and customer‑facing telemetry, including for customer‑managed and on‑prem environments.

ML Infra: GPU and model‑serving platforms for LLM inference with multi‑provider routing and support for on‑prem/air‑gapped deployments.

Platform (DevEx): CI/CD, paved paths, and core services that make shipping fast, safe, and consistent across teams.

Our mission is to deliver magical support experiences — AI agents working alongside humans to resolve issues quickly and accurately.

About the Role We're hiring a Senior Data Infrastructure Engineer to design, build, and operate the data systems that power Decagon's AI products. You'll own critical data pipelines and storage layers end‑to‑end, improve reliability and performance, and create paved paths that let every Decagon engineer work confidently with data at scale.

In this role, you will

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 our analytical data layer — 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.

Your background looks something like this

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.

Even better if you have

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

Compensation

$200K – $400K + Offers Equity

This range reflects the expected compensation for this role. Compensation within the range is determined based on experience, skills, and the scope of responsibilities, with flexibility for candidates who demonstrate exceptional impact.

In addition to base salary, we offer competitive equity. Final compensation may vary based on location within the United States.

Benefits

  • We proudly offer the following benefits for our full-time employees:
  • 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
  • Monthly stipend to support your wellness, lifestyle, and work-life balance
  • Daily lunches and snacks in the office to keep you at your best
  • Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)
  • These benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.

Where you’d work

From the office

About the company

Decagon

  • Industry: AI

Offices in San Francisco, United States, New York City, United States

Also hiring in Australia and London, United Kingdom

Your chances

Worth a look before you spend an evening tailoring a CV for it.

  • 21 checks run
  • 3 red flags

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14 checks

1 red flag

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7 checks

2 red flags

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  • Must-haves
Details13 facts · Role, Location, Compensation, Employment, Company
Tech stack
  • AWS
  • dbt
  • Kubernetes
  • Kafka
  • Azure
  • Spark
  • Databricks
  • Snowflake
  • Airflow
  • BigQuery
  • Flink
  • LLMs
Seniority
Senior
Type
Full-time
Equity
Equity offered
Industry
AI
Specialty
Data Engineering
Show 7 more factsShow less

Role

Category
Data & Analytics
Specialty
Data Engineering
Seniority
Senior
Experience
5+ years
Tech stack
  • AWS
  • dbt
  • Kubernetes
  • Kafka
  • Azure
  • Spark
  • Databricks
  • Snowflake
  • Airflow
  • BigQuery
  • Flink
  • LLMs

Location

Work model
Office
Region
United States
Offices
  • San Francisco, United States
  • New York City, United States

Compensation

Salary
$200,000 - 400,000 / year
Pay period
Annual
Equity
Equity offered

Employment

Type
Full-time

Company

Industry
AI

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