Agentic AI Engineer Intern

Docusign brings agreements to life. More than 1.8 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 the Docusign AI-native IAM platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM).

We are looking for a passionate and curious Agentic AI Engineer Intern to help build the next generation of autonomous AI workflows and multi-agent systems. In this role, you will work at the frontier of Generative AI, leveraging modern framework stacks like CrewAI, Python, SQL, and the Gemini ADK. You will collaborate closely with senior engineers to design, deploy, and evaluate autonomous agents capable of complex reasoning, tool usage, and task execution.

This internship offers deep hands‑on experience with LLMs, prompt engineering, agent orchestration, and evaluation frameworks.

This is an internship role for 3 months of duration.

This position is an individual contributor role reporting to the Sr. Manager, Data & Analytics.

• Design, build, and test collaborative AI agent workflows using CrewAI, Gemini ADK and Python
• Integrate Google’s Gemini ADK (and other modern LLM APIs) to power reasoning, function calling, and structured outputs
• Connect agents to databases (SQL), APIs, and internal tools to allow real-world execution and retrieval‑augmented generation (RAG)
• Craft, benchmark, and refine system prompts, agent roles, and task descriptions to maximize task success rates and reduce hallucinations
• Assist in establishing quantitative evals and measurement frameworks to benchmark agent performance, accuracy, latency, and cost efficiency
• Monitor agent execution traces, debug multi‑turn agent conversations, and implement fallbacks for robust behavior

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.

• Currently pursuing a Bachelor’s, Master’s, in Computer Science, Data Science, AI/ML, or a related technical field
• Graduating in December 2027 and May/June 2028
• Experience with Python and fundamental data structures
• Experience with SQL and relational database concepts
• Experience with Large Language Models (LLMs) and core concepts (tokenization, context windows, function calling/tool use)
• Experience with CrewAI or similar agentic frameworks (e.g., Lang Chain, Google ADK)
• This role is not eligible for CPT, OPT or sponsorship now or in the future

• Hands‑on experience with the Google ADK or Google Cloud Vertex AI platforms
• Prior experience writing automated tests or using LLM evaluation tools (e.g., Ragas, Deep Eval, Phoenix/Arize, or custom evaluation harnesses)
• Familiarity with vector databases, embeddings, or RAG architectures
• Active open‑source contributions or personal side projects involving AI agents

Pay for this position is based on a number of factors including geographic location and…