Sr. Data Platform Engineer

Company Overview

Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people’s lives. With intelligent agreement management, Docusign unleashes business-critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity. Using Docusign’s Intelligent Agreement Management platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM).

What you'll do

The Data and AI Platform Engineer will design, build, and operate our next‑generation data and AI platform, enabling high‑quality analytics, data science, and AI/ML capabilities at scale. Reporting to the Sr. Director, Data Platform and ML Operations, this role serves as a technical expert on Snowflake and AI infrastructure, with a strong focus on production‑grade reliability and performance. You will work closely with data engineers, data scientists, ML/AI engineers, BI developers, and business stakeholders to turn data and AI requirements into robust platforms, pipelines, and services. This position offers the opportunity to shape our data, ML, and AI architecture, influence best practices, and drive innovation across our Data Analytics Organisation.

 

This position is an individual contributor role reporting to the Sr. Director, Data Platform & ML Operations.

 

Responsibility

• Design, build, and maintain scalable, secure, high‑performing data and AI platforms using Snowflake and AI infrastructure components (e.g., feature stores, model registries, model serving endpoints)

• Own and optimize the Snowflake environment (warehouses, databases, schemas, roles, resource monitors) with a focus on performance tuning, cost optimization, and capacity planning for both data and AI workloads

• Stay current on Snowflake releases, the modern data stack, BI tooling, AI/ML, MLOps, and generative AI best practices and proactively recommend platform improvements

• Design, build, and operationalize AI capabilities in Snowflake using Snowflake Cortex and native Snowflake AI features to power governed, production‑grade conversational, retrieval‑augmented, and predictive applications

• Build and operate AI agents and workflows in Snowflake Cortex or similar platforms, integrating tools and context while optimizing prompt patterns to ensure reliable, high‑quality LLM outcomes

• Contribute to and evolve the overall data, ML, and AI architecture (warehouse, lake/lakehouse, streaming, feature and vector stores, model serving, AI app layers) while establishing and enforcing best practices for data modeling, AI/ML pipeline development, code reviews, testing, deployment, and documentation across the stack

• Automate infrastructure and deployment using CI/CD and Infrastructure‑as‑Code for data pipelines, ML workflows, and AI/LLM services

• Architect and manage AWS‑based data and AI infrastructure including S3‑backed data lakes, MWAA/Airflow environments, and supporting services for data ingestion, transformation, and model deployment

• Implement robust monitoring, logging, and cost‑management practices for AWS data and AI services to ensure platform reliability, security, and efficiency

• Collaborate with cloud, networking, security, compliance, and infrastructure teams to design resilient, scalable AWS architectures that integrate Snowflake, AI services, and downstream analytics/applications while implementing and maintaining strong data and AI governance (RBAC, masking, encryption, audit logging, responsible AI controls)

• Partner with data analysts, data scientists, ML/AI engineers, BI developers, and business stakeholders to translate data and AI requirements into scalable, secure technical solutions that deliver actionable insights and business value

Job Designation

Hybrid: Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation)

 

Positions at Docusign are assigned a job designation of either In Office, Hybrid or Remote and are specific to the role/job. Preferred job designations are not guaranteed when changing positions within Docusign. Docusign reserves the right to change a position's job designation depending on business needs and as permitted by local law.

What you bring

Basic

• Bachelor’s or Master’s degree in Computer Science or a related field

• 8+ years with