Lead AI Solutions Delivery Engineer

Docusign

Lead AI Solutions Delivery Engineer at DocuSign solving complex business problems using proprietary Agentic capabilities and third-party AI integrations. Collaborate with strategic enterprise customers to optimize agreement lifecycles.

Posted 6/8/2026full-timeRemote • Washington • 🇺🇸 United StatesSenior💰 $158,300 - $232,575 per yearWebsite

Tech Stack

Tools & technologies

CloudJavaMicroservicesPython

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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
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

Comp & perks

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

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

PythonJavaC++AI orchestration frameworksLLMsGenAI applicationsdata pipelinesmicroservicesAPIsDocusign

Soft Skills

strong communicationcustomer engagementcollaborationlearning postureproblem-solvingcustomer outcomes focustechnical trainingworkshop facilitationcross-functional teamworkcritical evaluation

Certifications

Bachelor's degree in Computer ScienceBachelor's degree in MathematicsBachelor's degree in Computer EngineeringBachelor's degree in StatisticsBachelor's degree in Operations Research