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AI Summary
About Workato
Workato transforms technology complexity into business opportunity. As the leader in enterprise orchestration, Workato helps businesses globally streamline operations by connecting data, processes, applications, and experiences. Its AI-powered platform enables teams to navigate complex workflows in real-time, driving efficiency and agility.
Trusted by a community of 400,000 global customers, Workato empowers organizations of every size to unlock new value and lead in today’s fast-changing world. Learn how Workato helps businesses of all sizes achieve more at workato.com.
Why join us?
Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company.
But, we also believe in balancing productivity with self-care. That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives.
If this sounds right up your alley, please submit an application. We look forward to getting to know you!
Also, feel free to check out why:
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Business Insider named us an “enterprise startup to bet your career on”
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Forbes’ Cloud 100 recognized us as one of the top 100 private cloud companies in the world
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Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America
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Quartz ranked us the #1 best company for remote workers
Responsibilities
We’re seeking a passionate Enterprise Agentic AI Intern to help us explore how Large Language Models (LLMs) can be extended into intelligent autonomous agents that work within enterprise systems. This internship offers hands-on experience in building, testing, and evaluating AI agents that use reasoning, memory, and tool access to solve real business problems.
In this role, you will also be responsible to:
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Design and test prototypes of AI agents that integrate with enterprise workflows (e.g., CRM, ERP, internal data systems).
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Build experiments to evaluate agent performance on multi-step reasoning and task completion.
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Integrate vector databases and implement retrieval-augmented generation (RAG) and agentic search.
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Optimize context management (windowing, summarization, long-term memory) and multi-agent collaboration patterns.
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Build and integrate tools that agents can invoke (tool registries, parameter forms, validation steps).
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Implement interoperability with external tools and third-party agents using the Model Context Protocol (MCP).
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Support dataset curation for agent training, fine-tuning, and evaluation.
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Collaborate with engineers and data scientists to develop evaluation pipelines and lightweight APIs for agent orchestration.
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Document experiments, visualize findings, and present insights to both technical and business stakeholders.
Requirements
Qualifications / Experience / Technical Skills
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Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or related field.
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Proficiency in Python and familiarity with Jupyter notebooks and Git.
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Understanding of machine learning fundamentals and natural language processing.
Bonus Points For
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Exposure to LLM APIs (OpenAI, Hugging Face, Anthropic, Cohere).
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Experience with frameworks for agents or orchestration (LangChain, LlamaIndex, Semantic Kernel, DSPy).
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Familiarity with PyTorch or TensorFlow.
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Knowledge of embeddings, retrieval-augmented generation (RAG), prompt design, or fine-tuning methods.
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Cloud platform exposure (AWS, GCP, or Azure).
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Hackathon, open-source, or project experience involving applied AI/ML.
Soft Skills / Personal Characteristics
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Strong analytical and problem-solving mindset.
(REQ ID: 2377)
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