Senior Sr. Data Scientist Engineer

About Us:

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.

Our Opportunity:

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 responsibilities include designing and maintaining high-quality data pipelines, performing data preprocessing and model experimentation, and deploying AI/ML services through APIs, microservices, and cloud-native platforms.

The role also focuses on system reliability, model evaluation, and continuous improvement. This includes developing quantitative and qualitative frameworks to assess model performance and LLM outputs, monitoring scalability and robustness of AI systems, proactively addressing technical risks and customer challenges, and contributing well-documented, modular, and maintainable AI/ML and data engineering solutions. Success in this role requires a commitment to operational excellence, innovation, and the ongoing advancement of AI capabilities across the organization.

Location: Remote - Pacific and Mountain Time Zones preferred.

You will make an impact by being responsible for:

• Build, evaluate, and deploy machine learning, deep learning, NLP, and LLM-based applications
• Develop LLM-powered agents and agentic AI systems
• Design prompt engineering strategies and LLM evaluation pipelines
• Implement retrieval-augmented generation (RAG) systems using vector databases and knowledge sources
• Design and maintain scalable, reliable data pipelines and datasets
• Perform data preprocessing, feature engineering, and model experimentation
• Deploy AI/ML services via APIs, microservices, and cloud infrastructure
• Monitor model performance and continuously improve system reliability and scalability
• Collaborate cross-functionally to translate customer needs into technical solutions
• Identify risks, manage customer pain points, and drive continuous improvement initiatives

You will be a great fit if you have:

• 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
• Experience with model training, evaluation, and experimentation
• Familiarity with prompt engineering, agent-based architectures, and retrieval systems
• Experience with APIs, distributed systems, and cloud platforms
• Ability to apply data science and AI techniques to real-world business problems

Benefits and perks you’ll appreciate:

• Flexible work schedule / remote roles
• Unlimited Personal Time Off
• 12 holidays off per year
• 4 days volunteer time off per year
• Variety of health care and well-being benefits
• Paid family/parental leave
• We are a designated “Best Place to Work” for 2 years in a row! Learn more here
• Newsweek’s Top 100 Most Loved Workplaces in America 2023 – Learn more here