Lead AI Solutions Delivery Engineer

This is a fully remote position, open to applicants in Washington.

📋 Description

• Design and spearhead cross-functional, customer-facing initiatives to create and implement a contemporary Agentic vision for Agreement Management business processes.

• Develop, construct, and deploy AI-enabled workflows and solutions that incorporate Docusign AI capabilities, including but not limited to Docusign's MCP Server and APIs, Docusign Web Forms supported by APIs to external systems, Custom Extractions, and Docusign skills in third-party agentic platforms (e.g., Docusign's integration with Open AI, Claude Cowork, Microsoft CoPilot, Harvey, and Legora) along with other similar customer Agentic Tech stacks for the automation and enhancement of customer business processes.

• Implement pioneering deployment strategies to validate, document, and standardize new Agentic implementation patterns, repeatable use cases, and toolkits.

• Conduct technical demonstrations, training sessions, and workshops tailored for both technical and non-technical audiences.

• Collaborate closely with customer stakeholders, Docusign product and engineering teams, success and services personnel, as well as third-party system integrators to convert open-ended operational business requirements into production-ready AI-enabled business solutions.

• Document repeatable deployment strategies and share insights and learnings with Docusign product and engineering teams.

• Create robust data pipelines, containerized microservices, distributed system architectures, and system context management repositories to ensure the reliable and accurate functioning of autonomous AI tools.

• Maintain a comprehensive understanding of the latest advancements in LLM capabilities, implementation patterns, and AI product development frameworks.

• Integrate field learnings, establish repeatable configuration scripts and deployment patterns, and formulate cross-functional, data-driven recommendations to deliver product consulting toolkits that create enterprise-deployable implementation guides.

• Collaborate with our Partner Enablement and broader partner organization to empower the partner ecosystem to implement well-architected solutions by sharing repeatable deployment best practices and blueprints.

• Critically assess both human-generated and AI-generated code for accuracy, quality, security, performance, and compliance within isolated cloud environments.

⛳️ Requirements

• Bachelor's or advanced degree in Computer Science, Mathematics, Computer Engineering, Statistics, Operations Research, or a related field, or equivalent practical experience.

• Over 12 years of experience in software engineering, deployment-centric engineering, or customer-oriented technical delivery roles within a recognized technology company, including AI-focused startups or scale-ups.

• At least 1.5 years of experience in implementing LLMs, production-quality GenAI applications, autonomous agents, or orchestration frameworks for production-level software.

• Experience collaborating directly with customers during proof of concepts (POCs), architecture evaluations, and technical assessments.

• Proficiency in programming languages such as Python, Java, C++, or foundational systems knowledge.

• Previous experience in roles such as forward-deployed engineer, customer-facing technical lead, startup CTO, enterprise architect, or software engineer with a consulting background.

• Experience deploying autonomous agents or AI orchestration frameworks in highly regulated sectors like finance or healthcare.

• Strong understanding of data security, compliance standards, and isolated enterprise cloud deployments.

• Ability to work collaboratively across functions and maintain a "love of learning" attitude to adapt to rapid advancements in the AI field.

• Willingness and capability to travel 25-50% of the time to customer locations as needed.

• Experience designing agent-based or LLM-powered applications that go beyond basic API calls, involving multi-step workflows, orchestration, and failure management.

• Excellent communication and customer engagement skills to facilitate customer discovery and articulate technical concepts to diverse stakeholders, including non-technical audiences.

• A commitment to driving and taking ownership of customer outcomes, rather than merely providing recommendations.

• A proactive approach and a "learning mindset" in the dynamic landscape of AI and LLMs, with the ability to adapt quickly.

• Enthusiasm for developing and managing AI agents in production, learning alongside customers, and sharing those insights with cross-functional teams.

🏝️ Benefits

• Paid Time Off: accrued time off, in addition to paid company holidays based on the region.

• Paid Parental Leave: up to six months off with your child following birth, adoption, or foster care placement.

• Comprehensive Health Benefits Plans: options for fully employer-paid and minimal employee contribution health plans available from the first day of employment.

• Retirement Plans: options for retirement and pension programs with potential employer contributions.

• Learning and Development: access to coaching, online courses, and educational reimbursements.

• Compassionate Care Leave: paid time off following the loss of a loved one or other significant life events.