Docusign
From Docusign's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
What you'll do Docusign operates global, always-on services.
Company Overview Docusign brings agreements to life. More than 1.8 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 the Docusign AI-native IAM platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM). What you'll do Docusign operates global, always-on services. To safeguard customer trust and empower our engineering teams, we are building the next generation of monitoring and troubleshooting capabilities.] You will lead the engineering organization behind our AI-powered observability platform. Built to complement existing tools like Grafana, Prometheus, and Clickhouse/Azure Data Explorer , this platform addresses the challenges of information overload by making observability accessible to everyone. You will manage a multidisciplinary team of backend engineers, machine learning engineers, and data scientists to build predictive, automated insights while running a highly critical service with strict SLAs. This positon is a apeople manager role reporting to the Senior Director, Software Engineering. Responsibility Manage high-throughput, real-time observability pipelines processing massive volumes of telemetry data across multi-region, multi-cloud environments Operate a Tier-0 data plane with strict SLOs, disciplined change management, and high availability requirements Serve as the observability backbone for every engineering team's reliability and velocity, dramatically reducing the time from "something's wrong" to "here's the problem" Set a clear 12-24 month vision for AIOps capabilities, focusing on automated troubleshooting workflows, proactive anomaly detection, and smart alert aggregation Bridge the gap between robust backend infrastructure and applied machine learning, ensuring models for auto-threshold estimation and pattern recognition are effectively trained and reliably deployed at scale Drive availability, durability, incident readiness, and disaster recovery for the observability plane; run regular resilience drills Lead, hire, and grow a senior-heavy team of backend engineers, ML engineers, and applied scientists. Build an architecture culture, clear career paths, and a high-judgment, high-ownership operating model Own the annual operating plan for the AIOps platform capacity, availability, and budget, meeting or beating committed SLOs/SLAs Drive the development of intelligent capabilities like automated impact analysis, ML-driven threshold estimation, and natural language interfaces to reduce alert noise and accelerate debugging Continually improve ingestion latency, query performance, storage efficiency, and cost per unit while maintaining reliability through traffic spikes and deploys Partner with SRE, Telemetry Platform, Security, Finance, and Product; make pragmatic build-vs-buy decisions; manage vendors and capacity commitments Lead on-call and incident command for the observability platform Job Designation Hybrid: Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation) Positions at Docusign are assigned a job designation of either In Office, Hybrid or Remote and are specific to the role/job. Preferred job designations are not guaranteed when changing positions within Docusign. Docusign reserves the right to change a position's job designation depending on business needs and as permitted by local law. What you bring Basic 12+ years in software/infra/platform engineering, including 6+ years operating high-scale, 24x7 back-end systems. 3+ years managing managers and senior ICs, specifically leading multidisciplinary teams across domains like backend engineering and machine learning. Proven ownership of mission-critical services with strict SLOs, incident management, and change control. Experience hiring, developing, and retaining senior/principal talent and building inclusive, high-trust teams. Preferred Familiarity with modern observability practices (metrics, logs, distributed tracing) and standards such as OpenTelemetry Experience leading teams that build, train, and deploy machine learning models in production environments for AIOps, anomaly detection, or predictive analytics Experience improving the performance and reliability of large telemetry/data pipelines at a multi-region scale Exposure to multi-cloud environments and Kubernetes-based platforms Wage Transparency Pay for this position is based on a number of factors including geographic location and may vary depending on job-related knowledge, skills, and experience. Based on applicable legislation, the below details pay ranges in the following locations: Washington, Maryland, New Jersey and New York (including NYC metro area): $202,100.00 - $299,625.00 base salary This role is also eligible for the following: 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). Global benefits provide options for the following: 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 Life at Docusign Working here Docusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do what’s right, every day. At Docusign, everything is equal. We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, you’ll be loved by us, our customers, and the world in which we live. Accommodation Docusign is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need such an accommodation, or a religious accommodation, during the application process, please contact us at accommodations@docusign.com. If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at taops@docusign.com for assistance. Applicant and Candidate Privacy Notice States Not Eligible for Employment This position is not eligible for employment in the following states: Alaska, Hawaii, Maine, Mississippi, North Dakota, South Dakota, Vermont, West Virginia and Wyoming. Equal Opportunity Employer It's important to us that we build a talented team that is as diverse as our customers and where all employees feel a deep sense of belonging and thrive. We encourage great talent who bring a range of perspectives to apply for our open positions. Docusign is an Equal Opportunity Employer and makes hiring decisions based on experience, skill, aptitude and a can-do approach. We will not discriminate based on race, ethnicity, color, age, sex, religion, national origin, ancestry, pregnancy, sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, registered domestic partner status, caregiver status, marital status, veteran or military status, or any other legally protected category. EEO Know Your Rights poster #LI-Hybrid Docusign operates global, always-on services. To safeguard customer trust and empower our engineering teams, we are building the next generation of monitoring and troubleshooting capabilities.] You will lead the engineering organization behind our AI-powered observability platform. Built to complement existing tools like Grafana, Prometheus, and Clickhouse/Azure Data Explorer , this platform addresses the challenges of information overload by making observability accessible to everyone. You will manage a multidisciplinary team of backend engineers, machine learning engineers, and data scientists to build predictive, automated insights while running a highly critical service with strict SLAs. This positon is a apeople manager role reporting to the Senior Director, Software Engineering. Responsibility Manage high-throughput, real-time observability pipelines processing massive volumes of telemetry data across multi-region, multi-cloud environments Operate a Tier-0 data plane with strict SLOs, disciplined change management, and high availability requirements Serve as the observability backbone for every engineering team's reliability and velocity, dramatically reducing the time from "something's wrong" to "here's the problem" Set a clear 12-24 month vision for AIOps capabilities, focusing on automated troubleshooting workflows, proactive anomaly detection, and smart alert aggregation Bridge the gap between robust backend infrastructure and applied machine learning, ensuring models for auto-threshold estimation and pattern recognition are effectively trained and reliably deployed at scale Drive availability, durability, incident readiness, and disaster recovery for the observability plane; run regular resilience drills Lead, hire, and grow a senior-heavy team of backend engineers, ML engineers, and applied scientists. Build an architecture culture, clear career paths, and a high-judgment, high-ownership operating model Own the annual operating plan for the AIOps platform capacity, availability, and budget, meeting or beating committed SLOs/SLAs Drive the development of intelligent capabilities like automated impact analysis, ML-driven threshold estimation, and natural language interfaces to reduce alert noise and accelerate debugging Continually improve ingestion latency, query performance, storage efficiency, and cost per unit while maintaining reliability through traffic spikes and deploys Partner with SRE, Telemetry Platform, Security, Finance, and Product; make pragmatic build-vs-buy decisions; manage vendors and capacity commitments Lead on-call and incident command for the observability platform Basic 12+ years in software/infra/platform engineering, including 6+ years operating high-scale, 24x7 back-end systems. 3+ years managing managers and senior ICs, specifically leading multidisciplinary teams across domains like backend engineering and machine learning. Proven ownership of mission-critical services with strict SLOs, incident management, and change control. Experience hiring, developing, and retaining senior/principal talent and building inclusive, high-trust teams. Preferred Familiarity with modern observability practices (metrics, logs, distributed tracing) and standards such as OpenTelemetry Experience leading teams that build, train, and deploy machine learning models in production environments for AIOps, anomaly detection, or predictive analytics Experience improving the performance and reliability of large telemetry/data pipelines at a multi-region scale Exposure to multi-cloud environments and Kubernetes-based platforms
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