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DocuSign is seeking an AI Solutions Delivery Engineer to work directly with enterprise customers on complex agreement management challenges using DocuSign's Agentic AI capabilities and third-party integrations. You will design and deploy AI-enabled workflows that integrate DocuSign's platform (MCP servers, APIs, custom extractions, skills) with leading AI ecosystems including OpenAI, Claude, and Microsoft CoPilot to automate and optimize customer business processes at scale.
Key responsibilities include designing cross-functional customer engagements to develop modern Agentic Agreement Management solutions; building and deploying AI workflows that integrate DocuSign capabilities with third-party systems; executing deployment "firsts" to prove out and productionize new Agentic patterns; running technical demos and workshops for diverse audiences; partnering with customer stakeholders, product teams, and system integrators to translate business requirements into production AI solutions; developing robust data pipelines, containerized microservices, and distributed architectures for autonomous AI tools; and synthesizing field learnings to establish repeatable deployment strategies and contribute insights back to product teams.
You will maintain deep knowledge of LLM capabilities and implementation patterns, evaluate code for correctness and security, and partner with the partner ecosystem to equip them with well-architected implementation guides and best practices.
Required: Bachelor's degree (or equivalent) in Computer Science, Mathematics, Engineering, Statistics, or related field; 12+ years software engineering or customer-facing technical delivery experience at established tech companies or AI-focused startups; 18-24 months implementing production-grade GenAI applications, autonomous agents, and orchestration frameworks; direct customer experience during POCs and architecture reviews; proficiency in Python, Java, C++, or systems fundamentals.
Preferred: Forward-deployed engineer, customer-facing technical lead, startup CTO, or consulting background; experience deploying autonomous agents in regulated environments (finance/healthcare); deep understanding of enterprise AI deployment patterns.
