Principal Software Engineer

Company Overview

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).

What you'll do

The Collaboration & Negotiation team is looking for a Principal Software Engineer with experience working on ML based features to help define, architect, and deliver the next generation of AI-powered contract redlining tools. As a Principal Engineer, you will spearhead the research, architecture, and development of reliable and performant AI-based systems that power our core AI Assisted Review offering. You will cover the feature lifecycle, from problem formulation, data gathering, and evaluation, to model architecture and integration with new and existing product features. Our team used to be part of Lexion, which was acquired by Docusign, and rewards working efficiently within a large organization, putting the customer needs first, collaborating with teammates and other teams, and mentoring junior engineers.

 

This position is an individual contributor role reporting to the Sr. Manager, Machine Learning.

 

Responsibility

• Spearhead the design, architecture, and development of robust and performant systems for AI powered contract review

• Lead the entire ML lifecycle, including problem formulation, data gathering, feature engineering, model architecture selection, training, evaluation, deployment, and monitoring

• Join customer calls and use insights from these to drive ML improvements and feature development

• Write high-quality, production-ready code for ML pipelines, APIs, and services

• Ensure ML model design and architecture is extensible across multiple product features and participate in technical design and code reviews with an ML/AI focus

• Collaborate with Product Management, UX Design, and other engineering teams to define model requirements and provide accurate estimates for ML development efforts

• Work closely with QA and ML Ops to devise efficient, scalable testing, validation, and continuous integration/continuous delivery (CI/CD) processes for ML artifacts

• Identify, propose, and implement process improvements specific to the MLOps and ML engineering workflow to continuously increase the team's productivity and efficiency

• Stay current with the latest research, development best practices, and advancements in Machine Learning (especially NLP/Generative AI) and share findings with the team

• Research and prototype new AI features, models, and technologies to improve contract redlining capabilities

• Raise issues proactively that might impact model performance, data quality, or delivery commitments

• Fix production issues related to model inference and data pipelines and maintain ML system stability

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

• 15+ years of software product development experience, with a minimum of 8 years focused on production-grade Engineering for AI-powered products

• Experience designing, developing, and deploying highly scalable, consumer-facing ML applications and services

• Back end development experience

• Experience with modern server-side development using modern programming languages like .NET (our preferred platform), JVM (Java/Scala), NodeJS, or others

• Experience with NoSQL and SQL

• Experience with Docker or other containerization technologies

• Experience working with scalable microservices

• Experience making improvements to existing large code base

• Experience using Git or other version control