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As a Lead AI Solutions Delivery 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 Activation.
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 third 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
Remote:
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.
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
1.5+ years of experience implementing LLMs, production-grade GenAI applications, autonomous agents, or orchestration frameworks for production level software
Experience working directly with customers during POCs, architecture reviews, and technical evaluations
Experience with Python, Java, C++, or systems fundamentals
Preferred
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 required to support the rapid development in the AI space
Willingness and ability to travel 25-50% of the time to customer sites as required
Experience designing agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling
Strong communication and customer engagement skills for conducting customer discovery and conveying and synthesizing technical concepts to or 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
Global benefits
Work Authorization Notice:
Please note that we do not provide visa sponsorship or immigration support for this position. Applicants must already be authorized to work in the United States on a full-time, permanent basis without the need for current or future sponsorship.
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