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 prospect. 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 : This position is an individual contributor role reporting to the Manager Data Engineering. - Responsibility

- Champion an AI-first mindset, embedding AI into data workflows, internal tools, and business processes
- Design and maintain AI-native data solutions and scalable data/AI pipelines for analytics, RAG, fine-tuning, and copilots
- Build and operate agentic workflows (e.g., Crew AI, LangGraph, AutoGen) for complex multi-step business processes
- Develop and run LLM-integrated pipelines using Claude, Glean, Gemini, Snowflake Cortex and enterprise copilots- Translate business problems into data + AI solutions that deliver clear, actionable business insights
- Design robust data architectures spanning batch, streaming, and AI inference layers
- Build Snowflake-based pipelines using Python, dbt, and Airflow for analytics and AI workloads
- Implement and maintain data ingestion and reverse-ETL using Fivetran and Hightouch.
- Model data for MDM, Marketing, Finance, and Customer Success (adoption, retention, telemetry)
- Manage AWS infrastructure (S3, EC2, IAM, Lambda, Step Functions, Glue) for data and AI platforms




- Enforce data privacy, governance, and compliance, including PII controls in Snowflake and AWS
- Implement data and AI observability with tools like Monte Carlo and Datadog
- Optimize SQL models and Python transformations to support feature stores and data products- Partner with stakeholders across functions to gather requirements and design end-to-end data + AI architectures
- Own and monitor solutions to meet SLAs, SLOs, data freshness, and business KPIs
- Maintain clear documentation for data platforms, AI systems, and architecture
- Troubleshoot and resolve data and AI issues, driving root-cause fixes
- Deliver work using Agile/Scrum, acting as a strong team player and mentor

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 Degree in Computer Science, Data Analytics, Information Systems, or a related technical field




- 8+ years of combined Data Engineering and AI/ML Engineering experience in production environments
- Expert-level SQL and Snowflake skills, including performance tuning and dimensional/relational modeling
- Strong Python skills for data pipelines and AI integration
- Proven experience building and shipping agentic AI workflows (e.g., Crew AI, LangGraph, AutoGen or similar) in production
- Experience with AI productivity and enterprise tools such as Claude, Glean, Gemini, Snowflake Cortex, GitHub Copilot, dbt Copilot, and other copilots
- Hands-on experience with Airflow and dbt, plus Fivetran (ingestion) and Hightouch (reverse-ETL) - Preferred
- 8+ years of dimensional and relational data modeling and OLAP data warehousing (Snowflake primary; Teradata/Redshift or similar a plus)
- 8+ years delivering ETL/ELT solutions from databases, SaaS platforms, APIs, flat files, and JSON using dbt, Matillion, and custom pipelines- Strong functional experience in MDM, Marketing attribution, Finance (AP/AR, invoicing), or Customer Success (adoption, retention, telemetry)
- Experience with data observability platforms such as Monte Carlo, Datadog, or Great Expectations
- Familiarity with data privacy regulations (e.g., GDPR, CCPA) and implementation of PII masking and role-based access controls
- Experience with AWS (S3, EC2, IAM, Lambda, Step Functions, Glue) and modern CI/CD practices (Git, pipelines, automated testing)
- Experience building BI dashboards and data products using Tableau, Looker, or equivalent
- Experience with transactional databases (OLTP) such as Oracle, SQL Server, or MySQL
- Experience creating ERDs with tools like SQLDBM, Erwin, dbdiagram.io, or equivalent
- Experience using Jira and Confluence in Scrum/Agile teams t

📌 Ai Engineer (Bengaluru)
🏢 Docusign
📍 Bengaluru