Senior Software Engineer

Docusign • Seattle, WA

37d • Hybrid

About The Position

Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people’s lives. With intelligent agreement management, Docusign unleashes business-critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity. Using Docusign’s Intelligent Agreement Management platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM).

Operating a reliable global service requires robust observability and automation. The Observability team builds the real‑time telemetry and AI/ML capabilities that power how engineers measure, visualize, investigate, and improve customer experience at scale.
This position is an indiviual contributor role reporting to the Senior Director, Software Engineering.

Requirements

• 8+ years of software engineering, with deep Python and SQL in production
• Experience building real‑time + batch pipelines with stringent SLAs and data quality controls
• Experience in time‑series analysis, anomaly detection, and forecasting for operational systems
• Experience deploying containerized services (Docker), Linux fundamentals, and CI/CD
• Experience with at least one time‑series/analytical store (ClickHouse, Postgres/TimescaleDB, columnar stores), and caching/NoSQL where appropriate
• Experience with workflow orchestration (Prefect, Airflow, or Dagster)

Nice To Haves

• Streaming platforms (Kafka/Redpanda/Pulsar) or equivalent messaging; schema management and idempotent/exactly‑once strategies
• Model serving and monitoring (custom FastAPI/Flask services, MLflow, KServe/Seldon); drift detection; shadow/canary rollouts
• Familiarity with observability tooling (OpenTelemetry, Prometheus, Grafana) and alerting best practices (SLOs, MTTR/MTTA)
• Exposure to LLMs and Hugging Face; interest in applying LLMs to ops guidance (RAG over telemetry/runbooks)
• Distributed systems fundamentals; cloud experience (GCP/AWS/Azure) and IaC
• Kubernetes experience (or willingness to ramp quickly)

Responsibilities

• Own end‑to‑end pipelines - from ingestion and feature engineering to training and real‑time/batch inference for operational time‑series use cases (metrics, logs, events)
• Design and operate anomaly‑detection and forecasting services (statistical/ML) that improve SLAs, reduce alert fatigue, and accelerate incident triage
• Build internal SDKs, metadata catalogs, and reusable ingestion frameworks that standardize access, enforce governance, and accelerate adoption across product and platform teams
• Harden data quality (sanity scoring, validation, drift checks), backfills, and replay strategies and define SLOs for data and models
• Partner with Applied Scientists to productionize models with pragmatic algorithms (e.g., tree‑based methods, classical TS) and selectively introduce deep learning where it pays off
• Optimize time‑series storage and compute (e.g., Prometheus, ClickHouse, Azure Data Explorer, columnar stores): partitioning, rollups, retention, and cost controls
• Integrate with the observability stack (OTel for signals; dashboards/alerts) and collaborate with SRE/infra to ensure performance and resilience
• Explore LLM‑assisted on‑call (RAG over logs/runbooks) to improve diagnosis and guidance; manage prompt safety, evals, and latency budget
• Deliver reliable, high‑throughput real‑time and batch data pipelines for billions of telemetry points/day
• Ship production‑ready services (APIs, jobs, workers) with clean contracts and strong observability
• Define data/model lifecycle: versioning, lineage, reproducibility, and automated evaluations
• Mentor early‑career engineers; champion platform ergonomics and documentation

Benefits

• Bonus: Sales personnel are eligible for variable incentive pay dependent on their achievement of pre-established sales goals. Non-Sales roles are eligible for a company bonus plan, which is calculated as a percentage of eligible wages and dependent on company performance.
• Stock: This role is eligible to receive Restricted Stock Units (RSUs).
• Paid Time Off: earned time off, as well as paid company holidays based on region
• Paid Parental Leave: take up to six months off with your child after birth, adoption or foster care placement
• Full Health Benefits Plans: options for 100% employer paid and minimum employee contribution health plans from day one of employment
• Retirement Plans: select retirement and pension programs with potential for employer contributions
• Learning and Development: options for coaching, online courses and education reimbursements
• Compassionate Care Leave: paid time off following the loss of a loved one and other life-changing events

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed