Note: The job is a remote job and is open to candidates in USA. Docusign provides intelligent agreement management solutions that help organizations create, commit to, and manage agreements. The Lead AI Solutions Delivery Engineer works directly with strategic enterprise customers to design, build, and deploy AI-enabled workflows using agentic capabilities, LLMs, APIs, and third-party integrations. The role also delivers technical demonstrations and workshops, develops reliable supporting architectures, and shares field insights with product, engineering, and partner teams.
Responsibilities
- 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
Skills
- 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
- 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
- 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
Benefits
- Bonus: Sales personnel are eligible for variable incentive pay dependent on their achievement of pre-established sales goals. Non-Sales roles are eligible for a company bonus plan, which is calculated as a percentage of eligible wages and dependent on company performance.
- Stock: This role is eligible to receive Restricted Stock Units (RSUs).
- 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
- Remote: Employee is not required to be in or near an office frequently and works from a designated remote work location for the majority of the time.
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