The industry's most advanced, most deployed agentic process automation system combines the power of AI, Automation, and RPA to deliver secure end-to-end enterprise agentic automation for mission-critical processes. Backed by NEA, Norwest and SoftBank VF.
About the role
This role designs, develops, and deploys scalable AI and data-driven solutions leveraging machine learning, deep learning, natural language processing (NLP), and large language models (LLMs). The position is responsible for building intelligent agent architectures, prompt-driven workflows, and retrieval-augmented generation (RAG) pipelines that integrate enterprise data sources and vector databases to deliver impactful business outcomes. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Master’s degree in Artificial Intelligence, Computer Science, Data Science, or related field
- Minimum 3-years experience in relevant fields
- Strong programming skills in Python, Java, SQL and data processing
- Experience working with structured and unstructured data
- Knowledge of machine learning, deep learning, NLP, and LLM systems
- Deep knowledge of MCP and A2A protocols
More about this role
Automation Anywhere is the leader in Agentic Process Automation (APA), transforming how work gets done with AI-powered automation. Its APA system, built on the industry’s first Process Reasoning Engine (PRE) and specialized AI agents, combines process discovery, RPA, end-to-end orchestration, document processing, and analytics—all delivered with enterprise-grade security and governance. Guided by its vision to fuel the future of work, Automation Anywhere helps organizations worldwide boost productivity, accelerate growth, and unleash human potential.
This role designs, develops, and deploys scalable AI and data-driven solutions leveraging machine learning, deep learning, natural language processing (NLP), and large language models (LLMs). The position is responsible for building intelligent agent architectures, prompt-driven workflows, and retrieval-augmented generation (RAG) pipelines that integrate enterprise data sources and vector databases to deliver impactful business outcomes.
Working cross-functionally with Engineering, Product Management, and customer-facing teams, this individual translates business and customer requirements into production-ready AI solutions. Key...
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