Senior Software Engineer, Data Infrastructure
Decagon · San Francisco
About this role
## About Decagon Decagon is a conversational AI platform empowering brands to deliver concierge customer experiences. Our technology helps enterprises deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and more. We’re an in-office company focused on excellence and velocity, guided by values like **Just Get It Done**, **Invent What Customers Want**, **Winner’s Mindset**, and **The Polymath Principle**. ## About the Team (Infrastructure) The Infrastructure team builds and operates the foundations powering Decagon: **networking, data, ML serving, developer platform, and real-time voice**. We organize around: - **Core Infra:** Cloud stack (networking, compute, storage, security, IaC) for reliability, scale, and cost efficiency - **Data Infra:** Streaming/batch data platforms for analytics/BI and customer-facing telemetry (including customer-managed/on-prem) - **ML Infra:** GPU + model-serving platforms for LLM inference (multi-provider routing; on-prem/air-gapped support) - **Platform (DevEx):** CI/CD, paved paths, and core services to ship fast, safely, and consistently ## Role: Senior Data Infrastructure Engineer You’ll design, build, and operate the data systems that power Decagon’s AI products—owning critical data pipelines and storage layers end-to-end, improving reliability/performance, and creating paved paths for engineers to work confidently with data at scale. ### What you’ll do - 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** using **Kafka, Flink, and Airflow** - Own the **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 to hit tight **p95/p99** targets (optimize data paths, caching/partitioning) - Lead **Infrastructure-as-Code (Terraform)** and **GitOps** practices for data systems (reduce drift with reusable modules + policy-as-code) - Participate in **on-call** and drive down toil via automation and elimination of recurring data issues ### Your background - **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 - Strong observability and incident response skills (e.g., **OpenTelemetry**, **Prometheus/Grafana**, **Datadog**) - Clear written communication; ability to turn ambiguous requirements into simple, reliable designs ### Even better if you have - **CDC** tooling (e.g., **Debezium**) and orchestration frameworks (**Airflow, Dagster, Prefect**) - Experience with **Spark** or **Dask** - Familiarity with cloud data warehouses (**Snowflake, BigQuery, Redshift, Databricks**) - Experience as an early **data/platform/infrastructure** engineer - Strong **Kubernetes** experience (GKE/EKS/AKS) and multi-cloud exposure (GCP/AWS/Azure) - Experience with **customer-managed deployments** ## Compensation - **$200K – $400K + Offers Equity** - Final compensation depends on experience, skills, and scope; may vary by location within the United St
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