Automation Engineer I

Key Responsibilities

• Solution Development & Implementation

• Build, configure, and maintain Robotic Process Automation (RPA) bots using Automation Anywhere (Control Room, Bot Creator, Bot Insight).

• Develop custom Python scripts for complex data manipulation, file processing, API integrations, and tasks beyond native bot actions.

• Leverage Unify Apps or similar low-code/integration platforms to create seamless triggers, user interfaces, and application-to-application workflows.

• Assist in incorporating AI/GenAI components (e.g., document extraction via IDP/IQ Bot, basic LLM API calls, prompt engineering, pattern recognition) to transform deterministic bots into cognitive automations.

• Testing, Deployment & Monitoring

• Conduct comprehensive unit testing, system integration testing (SIT), and participate in User Acceptance Testing (UAT) defect resolution.

• Support deployment into staging and production environments following standard CI/CD and release management processes.

• Monitor bot performance, review execution logs, troubleshoot runtime exceptions, and implement fixes to minimize downtime.

• Collaboration & Stakeholder Communication

• Partner with cross-functional teams and business analysts to analyze "as-is" manual workflows and translate them into technical "to-be" architectures.

• Create clear technical documentation, including Process Design Documents (PDD), Solution Design Documents (SDD), and operational runbooks.

• Provide clear, concise progress updates during daily standups and sprint planning ceremonies.

Requirements & Tech Stack

• RPA Platforms: Working knowledge or hands-on project exposure to Automation Anywhere (A2019 / A360 architecture, credential management, work queues).
• Programming: Proficient in Python (core libraries, data handling with pandas/json, interacting with REST APIs using requests).
• Platform Integration: Exposure to Unify Apps or comparable workflow orchestration platforms.
• AI Fundamentals: Foundational understanding of AI/ML principles, Intelligent Document Processing (IDP), and basic familiarity with API-driven AI services (e.g., OpenAI API, cloud vision/NLP APIs).
• Database & Web Basics: Foundational knowledge of SQL, basic web technologies (HTML, JSON, XML), and Git version control.

Qualifications

• Education & Certifications:

• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related quantitative field (or equivalent practical experience).

• Soft Skills & Core Attributes:

• Team-First Mindset: High receptivity to feedback, active participation in peer code reviews, and eagerness to learn from senior engineers.

• Communication Skills: Demonstrated ability to explain technical details clearly to non-technical teammates, both in written documentation and verbal discussions.

• Analytical Problem-Solving: Ability to deconstruct a broken workflow logically, isolate root causes, and iterate toward a stable fix.