Lead AI Architect

Docusign•San Francisco, CA

6h•Hybrid

About The Position

The Global Data Analytics (GDA) Team at Docusign is seeking a Lead, results-oriented AI Architect to drive the design, development, and implementation of Agentic AI / Gen AI solutions. This professional will define the strategic vision for these AI initiatives, leveraging various technologies to ensure they align with business objectives and meet high standards for scalability, security, and performance. This position is an individual contributor role reporting to the Sr. Director Data Engineering & Architecture

Requirements

12+ years of experience in software architecture and development related experience
3+ years of hands-on experience with AI/ML technologies
Experience with Python, R, Java, Scala, or C++
Experience with TensorFlow, PyTorch, Scikit-learn, and Keras
Experience with development and orchestration of autonomous agents
Experience with implementing graph neural networks (GNNs) and knowledge graph solutions
Experience with frameworks such as LangGraph and CrewAI for building and managing complex multi-agent systems
Experience with Glean for enterprise search and knowledge management solutions

Nice To Haves

Proven track record of leading large-scale AI implementations
Demonstrated success in leading and delivering large-scale AI implementations
Proficient in major platforms: AWS, Azure, and Google Cloud Platform
Practical skills with MLflow, Kubeflow, Docker, and Kubernetes for scalable MLOps workflows
Experience with Hadoop, Spark, Kafka, and Elasticsearch
Solid understanding of SQL, NoSQL, Snowflake, and modern Vector databases
Advanced proficiency in cloud data warehousing, data sharing, and analytics
Skill in developing APIs (REST, GraphQL) and designing microservices architecture
Experience in data transformation, modeling and testing
Knowledge of workflow orchestration and data pipeline automation
Proven proficiency in orchestrating collaborative AI agents and delegating tasks effectively
Experience with managing agent-to-agent communication protocols and workflow design
Advanced implementation experience utilizing enterprise knowledge bases
Deep knowledge of enterprise AI search, knowledge discovery, and workplace intelligence solutions
Exceptional analytical, problem-solving, and communication skills
Proven leadership, team management, and strategic business acumen
Highly adaptable to new technologies
PhD in AI, Machine Learning, or related field
Relevant industry certifications (e.g., AWS ML Specialty, Google Cloud ML Engineer)
Experience in NLP, Computer Vision, or Robotics
Deep knowledge of AI ethics, bias detection, and responsible deployment
Experience implementing solutions on edge computing and IoT devices
Familiarity with advanced agent development frameworks like AutoGen, LangChain, or Semantic Kernel

Responsibilities

Develop and execute comprehensive AI strategies and roadmaps aligned with core business objectives
Design robust, end-to-end AI architectures for complex applications and systems
Evaluate, select, and integrate appropriate AI technologies, frameworks, and platforms
Produce detailed technical specifications and architectural blueprints for all AI initiatives
Serve as the technical lead for cross-functional teams throughout the AI project development and implementation lifecycle
Provide expert guidance on machine learning models, algorithms, and high-performance data pipelines
Manage the seamless integration of new AI solutions with existing enterprise infrastructure
Instill and enforce best practices for the development, deployment, and ongoing maintenance of AI systems
Architect scalable data platforms specifically designed to support demanding AI/ML workloads
Establish and maintain data governance frameworks, ensuring strict adherence to data quality standards
Design and implement cloud-based AI infrastructure and strategic deployment mechanisms
Proactively optimize system performance and efficiently manage resource utilization
Work closely with data scientists, data engineers, and diverse business stakeholders to drive results
Translate high-level business requirements into clear, actionable, and robust technical AI solutions
Present complex architectural designs and strategic recommendations to executive leadership
Act as a mentor for junior team members and champion AI literacy and understanding across the organization

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

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