Company Overview Docusign brings agreements to life. More than 1.8 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 the Docusign AI-native IAM 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 As a AI Solution Deployment Engineer, you will be on the front lines, embedded directly with strategic enterprise customers to solve complex business problems using Docusign’s proprietary Agentic capabilities, third-party AI integrations, and existing tech stacks. You will bridge the gap between business and technology, defining customer workflows, designing bespoke architectures, writing code, and engineering prompts to deliver tangible business outcomes. You will leverage Docusign’s IAM Platform, Docusign and third Party MCP servers, APIs, and third party integrations with leading AI ecosystems (like OpenAI, Microsoft CoPilot, and Claude) to optimize enterprise agreement lifecycles against contract populations exceeding millions of agreements. By capturing insights from these field deployments, you will collaborate cross-functionally with Docusign’s product and engineering teams to shape our long-term AI roadmap. This role is a perfect fit if you thrive in client-facing environments and have a proven track record deploying GenAI and LLMs in production. This position is an individual contributor role reporting to the Sr. Director, Value Delivery Realization. Responsibility Design and lead cross functional customer-facing engagements to develop and deploy a modern Agentic vision of Agreement Management business processes Design, build, and deploy AI enabled workflows and solutions that integrate Docusign AI capabilities including but not limited to, Docusign’s MCP Server and APIs, Docusign Web Forms backed by APIs to third party systems, Custom Extractions, Docusign skills in 3rd party agentic platforms (e.g. Docusign’s integration with Open AI, Claude Cowork, Microsoft CoPilot, Harvey and Legora) and other similar customer Agentic Tech stacks to automate and optimize customer business processes Execute deployment 'firsts' to prove out, capture, and productionize new Agentic implementation patterns, repeatable use cases and toolkits Run technical demos, trainings, and workshops for technical and non-technical audiences Partner directly with customer stakeholders, Docusign product, engineering, success, services and partner team members and third party system integrators to translate open-ended operational business requirements into production level AI enabled business solutions Memorialize repeatable deployment strategies and contribute insights and learnings back to Docusign product and engineering teams Develop robust data pipelines, containerized microservices, distributed system architectures, and system context management repositories to ensure autonomous AI tools operate accurately and reliably Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks Synthesize field learnings, establish repeatable configuration scripts and deployment patterns, and develop cross functional data based recommendations to establish and deliver product consulting toolkits to establish enterprise-deployable implementation guides Partner with our Partner Enablement and larger partner organization to equip the partner ecosystem to implement well-architected solutions by contributing repeatable deployment best practices and blueprints Evaluate human and AI-generated code critically for correctness, quality, security, performance, and compliance within isolated cloud environments 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 Bachelor's or advanced degree in Computer Science, Mathematics, Computer Engineering, Statistics, Operations Research, etc.or equivalent practical experience 12+ years of experience in software engineering, deployment-focused engineering, or customer-facing technical delivery roles, in an established technology company, including AI focused startups or scale-ups 18-24 months of experience implementing LLMs, production-grade GenAI applications, autonomous agents, and or orchestration frameworks for production level software, with a preference for experience designing agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling Experience working directly with customers during POCs, architecture reviews, and technical evaluation Experience with Python, Java, C++ or systems fundamentals Preferred Strong communication and customer engagement skills for conducting customer discovery and conveying and synthesizing technical concepts to/from diverse stakeholders, including non-technical audiences A passion for driving and taking responsibility for customer outcomes, rather than just making customer recommendations A bias toward action and a “learning posture” in the ever changing world of AI and LLMs with the ability figure things out on the fly Excitement about building and operating AI agents in production, learning with customers, and then sharing those learnings with cross functional teams Prior experience as a forward deployed engineer, customer-facing technical lead, startup CTO, enterprise architect or software engineer with consulting experience Experience deploying autonomous agents or AI orchestration frameworks within highly regulated environments such as finance or healthcare Deep understanding of data security, compliance frameworks, and isolated enterprise cloud deployments Ability to collaborate cross functionally and “love of learning” posture to support the rapid development in the AI space Willingness and ability to travel 25–50% of the time to customer sites as required Life at Docusign Working here Docusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do what’s right, every day. At Docusign, everything is equal. We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, you’ll be loved by us, our customers, and the world in which we live. Accommodation Docusign is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need such an accommodation, or a religious accommodation, during the application process, please contact us at accommodations@docusign.com. If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at taops@docusign.com for assistance. Applicant and Candidate Privacy Notice #LI-Hybrid #LI-CD4 As a AI Solution Deployment Engineer, you will be on the front lines, embedded directly with strategic enterprise customers to solve complex business problems using Docusign’s proprietary Agentic capabilities, third-party AI integrations, and existing tech stacks. You will bridge the gap between business and technology, defining customer workflows, designing bespoke architectures, writing code, and engineering prompts to deliver tangible business outcomes. You will leverage Docusign’s IAM Platform, Docusign and third Party MCP servers, APIs, and third party integrations with leading AI ecosystems (like OpenAI, Microsoft CoPilot, and Claude) to optimize enterprise agreement lifecycles against contract populations exceeding millions of agreements. By capturing insights from these field deployments, you will collaborate cross-functionally with Docusign’s product and engineering teams to shape our long-term AI roadmap. This role is a perfect fit if you thrive in client-facing environments and have a proven track record deploying GenAI and LLMs in production. This position is an individual contributor role reporting to the Sr. Director, Value Delivery Realization. Responsibility Design and lead cross functional customer-facing engagements to develop and deploy a modern Agentic vision of Agreement Management business processes Design, build, and deploy AI enabled workflows and solutions that integrate Docusign AI capabilities including but not limited to, Docusign’s MCP Server and APIs, Docusign Web Forms backed by APIs to third party systems, Custom Extractions, Docusign skills in 3rd party agentic platforms (e.g. Docusign’s integration with Open AI, Claude Cowork, Microsoft CoPilot, Harvey and Legora) and other similar customer Agentic Tech stacks to automate and optimize customer business processes Execute deployment 'firsts' to prove out, capture, and productionize new Agentic implementation patterns, repeatable use cases and toolkits Run technical demos, trainings, and workshops for technical and non-technical audiences Partner directly with customer stakeholders, Docusign product, engineering, success, services and partner team members and third party system integrators to translate open-ended operational business requirements into production level AI enabled business solutions Memorialize repeatable deployment strategies and contribute insights and learnings back to Docusign product and engineering teams Develop robust data pipelines, containerized microservices, distributed system architectures, and system context management repositories to ensure autonomous AI tools operate accurately and reliably Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks Synthesize field learnings, establish repeatable configuration scripts and deployment patterns, and develop cross functional data based recommendations to establish and deliver product consulting toolkits to establish enterprise-deployable implementation guides Partner with our Partner Enablement and larger partner organization to equip the partner ecosystem to implement well-architected solutions by contributing repeatable deployment best practices and blueprints Evaluate human and AI-generated code critically for correctness, quality, security, performance, and compliance within isolated cloud environments Basic Bachelor's or advanced degree in Computer Science, Mathematics, Computer Engineering, Statistics, Operations Research, etc.or equivalent practical experience 12+ years of experience in software engineering, deployment-focused engineering, or customer-facing technical delivery roles, in an established technology company, including AI focused startups or scale-ups 18-24 months of experience implementing LLMs, production-grade GenAI applications, autonomous agents, and or orchestration frameworks for production level software, with a preference for experience designing agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling Experience working directly with customers during POCs, architecture reviews, and technical evaluation Experience with Python, Java, C++ or systems fundamentals Preferred Strong communication and customer engagement skills for conducting customer discovery and conveying and synthesizing technical concepts to/from diverse stakeholders, including non-technical audiences A passion for driving and taking responsibility for customer outcomes, rather than just making customer recommendations A bias toward action and a “learning posture” in the ever changing world of AI and LLMs with the ability figure things out on the fly Excitement about building and operating AI agents in production, learning with customers, and then sharing those learnings with cross functional teams Prior experience as a forward deployed engineer, customer-facing technical lead, startup CTO, enterprise architect or software engineer with consulting experience Experience deploying autonomous agents or AI orchestration frameworks within highly regulated environments such as finance or healthcare Deep understanding of data security, compliance frameworks, and isolated enterprise cloud deployments Ability to collaborate cross functionally and “love of learning” posture to support the rapid development in the AI space Willingness and ability to travel 25–50% of the time to customer sites as required
