IT & Software

Lead AI Solutions Deployment Engineer

DocuSign

London · England · United Kingdom

Overview

In this client-facing role, you will deploy GenAI and LLM-based solutions for enterprise customers, shaping AI-enabled workflows and integrations with Docusign and third-party AI ecosystems. You’ll design architectures, write code, and craft prompts to deliver measurable business outcomes. You’ll collaborate with product, engineering, and partners to propagate repeatable deployment patterns and contribute to the AI roadmap. The work combines technical delivery with strategic impact in a fast-moving AI space.

Responsibilities

  • Design and lead cross-functional, customer-facing engagements to implement an Agentic vision of Agreement Management
  • Build AI-enabled workflows integrating Docusign MCP Server, APIs, Web Forms, and third-party agentic platforms
  • Execute deployment firsts, develop repeatable use cases and toolkits
  • Run technical demos, trainings, and workshops for diverse audiences
  • Collaborate with customers, product, engineering, success, services, and partners to translate requirements into production AI solutions
  • Document repeatable deployment strategies and share learnings with product and engineering
  • Develop robust data pipelines, containerized microservices, and scalable architectures for autonomous AI tools
  • Stay abreast of LLM capabilities and AI product development stacks
  • Create deployment playbooks and reference implementations for enterprise deployment
  • Partner with Partner Enablement to extend best practices to the partner ecosystem
  • Assess code for correctness, security, and performance in isolated cloud environments

Key requirements
  • 12+ years in software engineering, deployment-focused roles or customer-facing technical delivery in tech companies
  • 18-24 months experience implementing LLMs and production-grade GenAI applications with multi-step workflows
  • Experience with Python, Java, C++ or systems fundamentals
  • Experience working with customers during POCs, architecture reviews, and technical evaluations
  • Strong communication and ability to explain technical concepts to non-technical audiences
  • Customer-centric and outcome-driven mindset
  • Bias toward action and continuous learning in AI/LLMs
  • LLM deployment and orchestration
  • Agent-based or autonomous AI workflows
  • Experience with AI integrations (OpenAI, Claude, Microsoft CoPilot, Harvey, Legora)

Reference: WJ-799_29574897

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