What you'll doAs a Software Engineer on the AI Platform team, you will architect and build the robust distributed systems and backend infrastructure that power global AI capabilities. This is a systems-first role where you will be responsible for the "pipes and engines" of our AI operations, ensuring that document processing, model serving, and data orchestration are reliable, resilient, and horizontally scalable. You will bridge the gap between core AI research and production-grade engineering, developing scalable platforms for autonomous agents, advanced retrieval systems, and automated model optimization.
This position is an individual contributor role reporting to the Director, Machine Learning Engineering
Responsibility- Build and maintain high-performance distributed systems to support large-scale model inference and data processing
- Design and build resilient, horizontally scalable backend services capable of handling high-throughput data processing and model interaction
- Develop the core infrastructure for model serving and inference runtimes, focusing on maximizing resource utilization and minimizing latency
- Architect resilient data ingestion and processing pipelines that handle massive datasets while ensuring data integrity, multi-tenant isolation, and high availability
- Optimize system performance, identify bottlenecks, and implement advanced monitoring (SLOs, SLAs) to ensure high reliability for mission-critical AI services
Job DesignationHybrid: 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 bringBasic- 5+ years of software engineering experience with a primary focus on distributed systems and scalable backend architecture
- Experience building, deploying, and maintaining ML models in high-traffic, production environments
- Experience with Python and professional experience with at least one other strongly-typed language (e.g., Java, Go, or C#)
- Experience with container orchestration (e.g., Kubernetes), messaging systems (e.g., Kafka, Service Bus), and high-performance database design
- Experience building production systems that operate at massive scale with strict uptime and latency requirements
- Bachelor's or Master's degree in Computer Science or a related technical field
Preferred- Experience with stateful workflow engines or distributed task queues (e.g., Temporal) for managing complex, multi-step AI processes
- Familiarity with frameworks designed for horizontal scaling of compute-intensive ML workloads (e.g., Ray, Spark)
- Expertise in Azure or GCP infrastructure, specifically around identity, security, and compliant networking (VNETs, PEPs)
- Experience building platform-level services for LLM orchestration, RAG architectures, and specialized prompt configuration layers
Wage TransparencyPay 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:
California: $146,400.00 - $235,375.00 base salary
Washington: $140,100.00 - $206,775.00 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
#LI-Hybrid
