Sr. AI 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

We are seeking an AI Engineer who can operate at the intersection of AI/ML, distributed systems, and enterprise business platforms. This role will help in the design and implementation of AI-driven capabilities across CRM, CPQ, Billing, and Revenue systems, enabling automation, intelligence, and scale across go-to-market workflows.

 

This is a hands-on technical role. You will architect, prototype, and productionize AI solutions while partnering closely with Product, Sales Ops, RevOps, Finance, and Engineering teams.

 

This position is an individual contributor role reporting to the Director, Engineering.

 

Responsibility

• Design and implement production-grade AI systems, including: agentic workflows, Retrieval-Augmented Generation (RAG), embedding and vector-search architectures and tool-calling and orchestration patterns

• Build AI services that integrate securely with enterprise systems of record (CRM, CPQ, Billing)

• Lead end-to-end AI solution delivery—from prototype to hardened, scalable production systems

• Define architectural standards for AI reliability, latency, observability, and cost efficiency

• Apply AI to core revenue workflows such as quote configuration and pricing recommendations, discounting and approval automation, contract intelligence and renewal forecasting and billing anomaly detection and revenue leakage prevention

• Understand lead-to-cash processes and translate business requirements into technical designsPartner with domain experts to ensure AI outputs are accurate, explainable, and trusted.

• Act as a Staff-level technical owner, influencing architecture across multiple teams

• Review designs, mentor senior engineers, and raise the engineering bar for AI systems

• Establish best practices for data access and governance, model evaluation and guardrails and security, compliance, and privacy (PII, SOC, GDPR)

• Partner closely with Product, Architecture, Security, Legal, and Data teams

• Serve as a technical advisor to leadership on AI strategy for GTM systems

• Communicate complex AI concepts clearly to both technical and non-technical stakeholders

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

• 8+ years of professional back-end software engineering experience
• 3+ years in AI/ML engineering, LLM-based systems, or advanced SaaS automation
• Experience building scalable, production-grade distributed systems using microservice architecture
• Experience in developing using AI tools like Copilot, Cursor, or Claude, and able to set up a framework to improve Eng team productivity
• Experience with Go or a similar language
• Experience working with Python for AI/ML modeling, experimentation, and prototyping

Preferred

• Proven experience designing and building AI-driven solutions for CPQ (Configure, Price, Quote) platforms         
• Strong understanding of subscription-based B2B business models (eg Recurring revenue, Usage-based pricing, etc)
• Experience with framework/architecture set-ups to build an agentic solution for a subscription-based industry in CPQ domain
• Experience building AI services that integrate with enterprise systems of record (CRM, CPQ, Billing).
• Deep understanding of LLM concepts and interworking
• Deep understanding of LangChain/LangGraph
• Experience Implementing agentic workflows to impro