Workato is looking to explore how Large Language Models (LLMs) can be extended into intelligent autonomous agents that work within enterprise systems to solve real business problems.
Requirements
- Proficiency in Python and familiarity with Jupyter notebooks and Git.
- Understanding of machine learning fundamentals and natural language processing.
- Exposure to LLM APIs (OpenAI, Hugging Face, Anthropic, Cohere).
- Experience with frameworks for agents or orchestration (LangChain, LlamaIndex, Semantic Kernel, DSPy).
- Familiarity with PyTorch or TensorFlow.
- Knowledge of embeddings, retrieval-augmented generation (RAG), prompt design, or fine-tuning methods.
- Cloud platform exposure (AWS, GCP, or Azure).
Responsibilities
- Design and test prototypes of AI agents that integrate with enterprise workflows (e.g., CRM, ERP, internal data systems).
- Build experiments to evaluate agent performance on multi-step reasoning and task completion.
- Integrate vector databases and implement retrieval-augmented generation (RAG) and agentic search.
- Optimize context management (windowing, summarization, long-term memory) and multi-agent collaboration patterns.
- Build and integrate tools that agents can invoke (tool registries, parameter forms, validation steps).
- Implement interoperability with external tools and third-party agents using the Model Context Protocol (MCP).
- Support dataset curation for agent training, fine-tuning, and evaluation.
Other
- Currently pursuing a Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or related field.
- Strong analytical and problem-solving mindset.
- Collaborate with engineers and data scientists to develop evaluation pipelines and lightweight APIs for agent orchestration.
- Document experiments, visualize findings, and present insights to both technical and business stakeholders.
- Balancing productivity with self-care in a flexible, trust-oriented culture.
