Software Engineer Intern

Docusign • Seattle, WA

3d • Hybrid

About The Position

Docusign brings agreements to life by harnessing the power of intelligent agreement management to unlock business-critical data from documents and connect it to systems of record. Our AI Applications team within the AI Engineering organization builds ML-powered product experiences from document understanding to intelligent workflows and, increasingly, AI agents that help customers work smarter. As an MLE Intern - AI Applications, you will help design, prototype, and ship ML-driven application features, including new capabilities on our AI agent framework and document understanding features for clauses and extractions. You'll collaborate closely with applied scientists, product managers, and engineers to turn research ideas into customer-ready features in the Docusign Agreement Cloud. This is an internship role for 5 months of duration.

Requirements

• Currently enrolled in a Bachelor's degree program in a relevant field with an expected graduation date between December 2027 and May/June 2028
• Coursework in Computer Science, Computer Engineering, or a related technical discipline
• Experience in Python for backend and/or machine learning development; familiarity with another language such as C#, Java, or TypeScript/JavaScript
• Experience with data structures, algorithms, and core software engineering fundamentals (testing, debugging, code reviews, version control)
• Experience from coursework, projects, or prior internships building applications or services that consume APIs or data pipelines
• Ability to work from the Seattle, WA hub location in a hybrid setup (regular in-office presence) for the duration of the 12-week internship, in alignment with Docusign's intern residency and on-site work policy

Nice To Haves

• Previous internship or substantial project experience in software engineering, data engineering, or machine learning
• Academic projects or coursework involving Machine Learning, Natural Language Processing, information extraction, or document understanding
• Experience working with one or more ML frameworks or libraries (e.g., PyTorch, TensorFlow, scikit-learn) and associated tooling for experimentation (e.g., Jupyter, notebooks, experiment tracking)
• Familiarity with modern LLM and agent concepts (e.g., retrieval-augmented generation, tools/plug-ins, orchestration frameworks such as LangChain, semantic kernel, or similar)
• Exposure to building or integrating RESTful and/or gRPC APIs and working with JSON- or protobuf-based services
• Experience with version control (Git) and collaborative development workflows (code reviews, pull requests)
• Comfort working in a cloud-based environment, preferably Azure, and with containerization technologies like Kubernetes
• Strong communication skills and an interest in collaborating with cross-functional partners to deliver user-facing features

Responsibilities

• Implement and iterate on ML-powered application features under the guidance of senior engineers, such as new capabilities in our AI agent framework or clause/extraction experiences in Docusign products
• Contribute to end-to-end ML feature workflows: data preparation, model integration, evaluation, and deployment into customer-facing experiences
• Integrate ML services into backend APIs and/or product surfaces, following best practices for reliability, security, and observability
• Build and maintain Python-based services and components that run on Kubernetes in Azure as part of our ML application stack
• Instrument features with logging, metrics, and basic dashboards to monitor performance and user impact
• Write clean, maintainable, and well-tested code, including unit and integration tests, as part of our standard development and review process
• Collaborate with cross-functional partners (Product, Design, QA, and other engineering teams) to clarify requirements, demo progress, and incorporate feedback
• Proactively learn new tools and techniques (e.g., LLMs, agent frameworks, prompt engineering, vector search, orchestration libraries) and share learnings with the team

Benefits

• 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: Intern