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 Generative AI Engineer will design and build AI-powered Quality Agents that automate the end-to-end Software Test Life Cycle (STLC), significantly boosting QA productivity through advanced test case generation, script automation, and execution workflows. The engineer will embed generative AI capabilities across the STLC by enhancing test automation frameworks, integrating with CI/CD pipelines, and enabling quality dashboards to support faster, smarter, and more reliable software delivery. This position is an individual contributor role reporting to the Senior Manager SDET. Responsibility Design and orchestrate specialized AI agents for automated test case, script, and data generation and test execution agents Develop LLM-powered assistants for test execution insights and defect analysis Build conversational chatbots for real-time guidance and natural-language test transactions Implement self-healing automation and RAG solutions using test logs and requirements Integrate AI capabilities into CI/CD pipelines and React-based quality dashboards Collaborate with cross-functional teams to enable AI-assisted, left-shift quality practices Build autonomous and workflow-based agents using CrewAI or similar agentic frameworks, and support agentic AI platforms Implement prompt engineering best practices to minimize token usage and improve output accuracy; contribute to a centralized prompt library Document processes, models, and code to ensure maintainability and reproducibility Collaborate with quality teams and product management teams to translate requirements into effective technical solutions Contribute to GenAI projects from ideation through deployment, iteration, and evaluation of LLM performance Assess building vs. buying the relevant tool and adopt the right tooling for the team Mentor junior team members and be responsible for delivering hands-on delivery along with leading the AI development team Build AI evaluation tools to certify the accuracy, performance, and fact checks Communicate to the broader team well and drive the adoption strategies Communicate clear statistics weekly to all stakeholders 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 Experience building GenAI applications (LLM orchestration, RAG, prompt engineering) Experience with Python, React, and orchestration frameworks like Crew.ai or Langgraph Experience with vector databases and ML-based models for non-text data Experience with AWS/Azure, Docker, Kubernetes, and automated CI/CD/MLOps pipelines Bachelor’s or Master’s in Computer Science with 5+ years of relevant experience Experience with key AWS services including VPC, IAM, and ECS, S3, Lambda Preferred Strong commitment to engineering excellence through automation, innovation, and documentation and presentations to stakeholders One or more certifications such as Cloud, Solution Architect, Technical Architect, or GenAI-related certifications Proficiency in cloud platforms such as AWS and Azure Strong problem-solving skills and the ability to think creatively Strong collaboration skills in cross-functional teams (Product, Design, ML, Data Engineering) Ability to explain complex GenAI concepts to both technical and non-technical stakeholders Integrating test cases with Playwright or UiPath Life at Docusign Working here Docusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do what’s right, every day. At Docusign, everything is equal. We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, you’ll be loved by us, our customers, and the world in which we live. Accommodation Docusign is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need such an accommodation, or a religious accommodation, during the application process, please contact us at accommodations@docusign.com. If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at taops@docusign.com for assistance. Applicant and Candidate Privacy Notice #LI-Hybrid #LI-SA4
AI Engineer
DocuSign · Enterprise · Bangalore, India · IT Infrastructure & Operations
AI Engineer at DocuSign focused on building Generative AI agents to automate the Software Test Life Cycle (STLC), including test case generation, script automation, and execution. The role involves integrating LLM capabilities, RAG, prompt engineering, and agentic frameworks into CI/CD pipelines and quality dashboards.
What you'd actually do
- Design and orchestrate specialized AI agents for automated test case, script, and data generation and test execution agents
- Develop LLM-powered assistants for test execution insights and defect analysis
- Build conversational chatbots for real-time guidance and natural-language test transactions
- Implement self-healing automation and RAG solutions using test logs and requirements
- Integrate AI capabilities into CI/CD pipelines and React-based quality dashboards
Skills
Required
- Python
- React
- Crew.ai or Langgraph
- vector databases
- AWS/Azure
- Docker
- Kubernetes
- CI/CD/MLOps pipelines
- GenAI applications
- LLM orchestration
- RAG
- prompt engineering
Nice to have
- Playwright
- UiPath
- Cloud certifications
- Solution Architect certifications
- Technical Architect certifications
- GenAI-related certifications
What the JD emphasized
- Basic Experience building GenAI applications
- Experience with Python, React, and orchestration frameworks like Crew.ai or Langgraph
- Experience with vector databases and ML-based models for non-text data
- Experience with AWS/Azure, Docker, Kubernetes, and automated CI/CD/MLOps pipelines
- Bachelor’s or Master’s in Computer Science with 5+ years of relevant experience
Other signals
- design and build AI-powered Quality Agents
- automate the end-to-end Software Test Life Cycle
- embed generative AI capabilities across the STLC
- Build autonomous and workflow-based agents using CrewAI or similar agentic frameworks