Software Engineer - AI

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).

We are seeking a Software Engineer to design, build, and scale intelligent, enterprise-grade software solutions, with a strong focus on agentic AI systems and complex integrations across Legal Technology and Docusign platforms. This role is a hands-on engineering position requiring deep expertise in software design, distributed systems, APIs, and AI-enabled architectures. The Software Engineer will develop and operate custom-built applications, AI agents, middleware services, and integration frameworks that connect core Legal Technology and Docusign platforms with enterprise and external systems. A key aspect of this role is the application of agentic AI patterns, including orchestration, tool-using agents, Retrieval-Augmented Generation (RAG), and workflow automation. This role partners closely with Product Management, Enterprise Architecture, and Legal Technology stakeholders but remains fundamentally an engineering role, accountable for code quality, system reliability, scalability, and security. This position is n individual contributor role reporting to the Senior Director, Application Engineering.

Conduct applied AI research to translate theoretical GenAI advancements into production-ready software features Lead Technical Feasibility Studies and rapid prototyping to provide the engineering foundation for "build vs. buy" architectural decisions Engineer Production-Grade NLP algorithms and information retrieval systems using SpaCy, NLTK, and Hugging Face to drive core product capabilities Design, build, and maintain scalable RAG architectures that connect foundational Large Language Models (LLMs) to proprietary enterprise databases Evaluate and apply appropriate embedding models, vector databases, and LLMs based on cost, latency, security, and performance requirements Build enterprise-grade conversational interfaces and analytical AI tools (QueryGPT) that interface directly with structured data systems via custom middleware Design and Build autonomous multi-agent frameworks (e.g., CrewAI, LangGraph) and scalable agentic platforms, focusing on distributed system architecture and secure execution environments Develop Custom Extensions and API-based integrations for LLM models, creating sophisticated AI assistants through backend systems programming Execute Model Engineering through supervised fine-tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF) to optimize model weight distribution for scalability and reliability Develop algorithmic prompt-chaining logic and maintain a centralized, version-controlled prompt library integrated into the CI/CD pipeline Architect and Develop end-to-end evaluation pipelines for LLMs/SLMs, Engineering complex telemetry to capture performance, quantization efficiency, and fine-tuning convergence metrics Own the technical documentation, code maintainability, and reproducibility of the AI infrastructure, ensuring alignment with engineering excellence standards 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