Decagon
Conversational AI
SeniorSoftwareEngineer,DataInfrastructure
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optimal for Senior candidates.
“Senior Software Engineer, Data Infrastructure at Decagon. Skills: Data Infrastructure, Streaming Systems, Kafka, Flink, ClickHouse. Design and implement high-throughput data pipelines and streaming systems. Build and operate real-time and batch ingestion infrastructure”
What You'll Achieve.
Deliver high-scale, low-latency systems with clear SLOs and great developer ergonomics; Ensure reliability, scale, and cost efficiency; Power analytics and customer-facing telemetry; Support on-prem/air-gapped deployments; Make shipping fast, safe, and consistent across teams; Deliver magical support experiences — AI agents working alongside humans to resolve issues quickly and accurately; Own critical data pipelines and storage layers end-to-end; Improve reliability and performance; Create paved paths that let every Decagon engineer work confidently with data at scale; Hit tight p95/p99 targets; Reduce drift with reusable modules and policy-as-code
Industry & Context.
Elimination of recurring data issues
On-call
What They're Looking For.
Must Have
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 incident response discipline, Clear written communication and the ability to turn ambiguous data requirements into simple, reliable designs
Nice to 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, Kubernetes experience (GKE/EKS/AKS) and multi-cloud exposure (GCP, AWS, Azure), Experience with customer-managed deployments
What You'll Do.
Design and implement high-throughput data pipelines and streaming systems
Build and operate real-time and batch ingestion infrastructure
Own analytical data layer — schema design
and cost optimization
Partner with research and product teams to architect data solutions
Tune pipeline and query latencies
Lead infrastructure-as-code (Terraform) and GitOps practices
Participate in on-call and drive down toil through automation
How You'll Work.
Team & Collaboration
Partner closely with product, data, and ML to deliver high-scale, low-latency systems; Partner with research and product teams to architect data solutions
Communication Scope
Clear written communication
Full Job 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. ABOUT THE 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
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